Triple
T14001611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirstie Alley |
E336838
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Alley
Alley is a surname most notably associated with American actress Kirstie Alley.
|
E1073771
|
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: Alley | Statement: [Kirstie Alley, familyName, Alley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alley Context triple: [Kirstie Alley, familyName, Alley]
-
A.
Ramp Alley
Ramp Alley is a specific area or feature within Catherine Park, likely a pathway or section characterized by an inclined ramp.
-
B.
Dutch Alley
Dutch Alley is a distinctive section of New Orleans’ historic French Market known for its art, culture, and local shops.
-
C.
Ashburn Alley
Ashburn Alley is a fan-friendly concourse and gathering area at Citizens Bank Park featuring food, games, team history displays, and views of the field.
-
D.
Mule Alley
Mule Alley is a redeveloped historic street within Fort Worth’s Stockyards district, featuring restored brick buildings that now house shops, restaurants, and entertainment venues.
-
E.
Santee Alley
Santee Alley is a bustling open-air marketplace in downtown Los Angeles known for its dense concentration of discount clothing, accessories, and knockoff goods.
- 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: Alley Triple: [Kirstie Alley, familyName, Alley]
Generated description
Alley is a surname most notably associated with American actress Kirstie Alley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alley Target entity description: Alley is a surname most notably associated with American actress Kirstie Alley.
-
A.
Ramp Alley
Ramp Alley is a specific area or feature within Catherine Park, likely a pathway or section characterized by an inclined ramp.
-
B.
Dutch Alley
Dutch Alley is a distinctive section of New Orleans’ historic French Market known for its art, culture, and local shops.
-
C.
Ashburn Alley
Ashburn Alley is a fan-friendly concourse and gathering area at Citizens Bank Park featuring food, games, team history displays, and views of the field.
-
D.
Mule Alley
Mule Alley is a redeveloped historic street within Fort Worth’s Stockyards district, featuring restored brick buildings that now house shops, restaurants, and entertainment venues.
-
E.
Santee Alley
Santee Alley is a bustling open-air marketplace in downtown Los Angeles known for its dense concentration of discount clothing, accessories, and knockoff goods.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed06a50819093ddc64f55050689 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbaca180988190bbfc93bd708688d6 |
completed | May 6, 2026, 9:03 p.m. |
| NEDg | Description generation | batch_69fbae8f83f481909ac16d4bb66ea79d |
completed | May 6, 2026, 9:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbaf702c94819095347e2599ae9931 |
completed | May 6, 2026, 9:15 p.m. |
Created at: April 9, 2026, 10:19 p.m.