Triple
T3296549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariska Hargitay |
E69229
|
entity |
| Predicate | televisionSeries |
P3279
|
FINISHED |
| Object |
Downtown
Downtown is an American television series featuring Mariska Hargitay in a leading role.
|
E344044
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Downtown | Statement: [Mariska Hargitay, televisionSeries, Downtown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Downtown Context triple: [Mariska Hargitay, televisionSeries, Downtown]
-
A.
City Center
City Center is a historic performing arts venue in Midtown Manhattan, best known for its dance, theater, and music programming.
-
B.
Downtown Center
Downtown Center is a Pensacola State College campus located in downtown Pensacola that offers higher education courses and workforce training programs.
-
C.
Central City
Central City is a historic Colorado mining town famed for its boom during the mid-19th-century gold rush and its well-preserved Victorian-era architecture.
-
D.
Central City
Central City is a major urban area in New Orleans known for its historic neighborhoods, cultural diversity, and role in the city’s social and commercial life.
-
E.
Midtown
Midtown is a major commercial and entertainment district in central Manhattan, New York City, known for its dense concentration of skyscrapers, corporate headquarters, and iconic landmarks like Times Square.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Downtown Triple: [Mariska Hargitay, televisionSeries, Downtown]
Generated description
Downtown is an American television series featuring Mariska Hargitay in a leading role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Downtown Target entity description: Downtown is an American television series featuring Mariska Hargitay in a leading role.
-
A.
City Center
City Center is a historic performing arts venue in Midtown Manhattan, best known for its dance, theater, and music programming.
-
B.
Downtown Center
Downtown Center is a Pensacola State College campus located in downtown Pensacola that offers higher education courses and workforce training programs.
-
C.
Central City
Central City is a historic Colorado mining town famed for its boom during the mid-19th-century gold rush and its well-preserved Victorian-era architecture.
-
D.
Central City
Central City is a major urban area in New Orleans known for its historic neighborhoods, cultural diversity, and role in the city’s social and commercial life.
-
E.
Midtown
Midtown is a major commercial and entertainment district in central Manhattan, New York City, known for its dense concentration of skyscrapers, corporate headquarters, and iconic landmarks like Times Square.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb078f3dc8190afb624f62894e48f |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e86e867c8190a1e5042a4d4d92cb |
completed | March 12, 2026, 4:23 p.m. |
| NEDg | Description generation | batch_69b2e8e42ecc8190b81d1b64f9fba0c1 |
completed | March 12, 2026, 4:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2e954ec18819096f31feb9e985b6a |
completed | March 12, 2026, 4:27 p.m. |
Created at: March 8, 2026, 3:10 p.m.