Triple
T6693626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas urban area |
E152689
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object |
Anna
Anna is a small suburban city within the greater Dallas metropolitan area in Texas.
|
E301921
|
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: Anna | Statement: [Dallas urban area, hasSuburb, Anna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Context triple: [Dallas urban area, hasSuburb, Anna]
-
A.
Anna
Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
-
B.
Anna
Anna is a central female character in the comedy Western film "A Million Ways to Die in the West," portrayed as a sharp-shooting, quick-witted woman who helps the protagonist toughen up in the dangerous frontier.
-
C.
Anna
Anna is the given name of pioneering Chinese American actress Anna May Wong, a trailblazing early Hollywood star and fashion icon.
-
D.
Anna
Anna is a character from the video game "Surfacing," likely serving as a key figure in the game's narrative or player interactions.
-
E.
Anna
Anna is a spirited and optimistic princess from Disney's animated film "Frozen," known for her bravery, loyalty, and deep love for her sister Elsa.
- 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: Anna Triple: [Dallas urban area, hasSuburb, Anna]
Generated description
Anna is a small suburban city within the greater Dallas metropolitan area in Texas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anna Target entity description: Anna is a small suburban city within the greater Dallas metropolitan area in Texas.
-
A.
Anna
chosen
Anna is a small city in north-central Texas that forms part of the fast-growing suburban region north of Dallas.
-
B.
Anna
Anna is a character from the "Predator" franchise, appearing as one of the human figures caught up in the deadly encounters with the extraterrestrial hunter.
-
C.
Anna
Anna is a woman whose full name is Mrs. Anna Smith.
-
D.
Anna
Anna is a central female character in the comedy Western film "A Million Ways to Die in the West," portrayed as a sharp-shooting, quick-witted woman who helps the protagonist toughen up in the dangerous frontier.
-
E.
Anna
Anna is a feminine given name of Hebrew origin meaning "grace" or "favor," widely used across many cultures and languages.
- F. None of above.
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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6b1955e448190adbfed7dc28f8c52 |
completed | March 27, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f79f1718819098d8a6d08bf7f919 |
completed | March 27, 2026, 9:33 p.m. |
| NEDg | Description generation | batch_69c6f8b1e1f48190bc9058a8a21a4a62 |
completed | March 27, 2026, 9:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f9441d74819098f0639a29fdeb5e |
completed | March 27, 2026, 9:40 p.m. |
Created at: March 27, 2026, 2:05 p.m.