Triple
T8569904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiler Peck |
E202901
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Tiler
Tiler is the first name of Tiler Peck, a renowned American ballet dancer and principal with the New York City Ballet.
|
E742465
|
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: Tiler | Statement: [Tiler Peck, givenName, Tiler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiler Context triple: [Tiler Peck, givenName, Tiler]
-
A.
Grand Tiler
Grand Tiler is a senior Masonic lodge officer responsible for guarding the entrance and ensuring the privacy and security of lodge meetings.
-
B.
House of Tiles
House of Tiles is a historic Baroque palace in Mexico City famed for its façade covered in blue-and-white Puebla tiles and its current use as a landmark restaurant and cultural venue.
-
C.
Tilos
Tilos is a small Greek island in the southeastern Aegean Sea, known for its unspoiled nature, rich biodiversity, and tranquil, less-touristed atmosphere.
-
D.
Taliedo
Taliedo is a district in Milan, Italy, historically known for its aviation industry and the Caproni aircraft manufacturing facilities.
-
E.
Tilelli
Tilelli is a surname most notably associated with retired U.S. Army General John H. Tilelli Jr.
- 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: Tiler Triple: [Tiler Peck, givenName, Tiler]
Generated description
Tiler is the first name of Tiler Peck, a renowned American ballet dancer and principal with the New York City Ballet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tiler Target entity description: Tiler is the first name of Tiler Peck, a renowned American ballet dancer and principal with the New York City Ballet.
-
A.
Grand Tiler
Grand Tiler is a senior Masonic lodge officer responsible for guarding the entrance and ensuring the privacy and security of lodge meetings.
-
B.
House of Tiles
House of Tiles is a historic Baroque palace in Mexico City famed for its façade covered in blue-and-white Puebla tiles and its current use as a landmark restaurant and cultural venue.
-
C.
Tilos
Tilos is a small Greek island in the southeastern Aegean Sea, known for its unspoiled nature, rich biodiversity, and tranquil, less-touristed atmosphere.
-
D.
Taliedo
Taliedo is a district in Milan, Italy, historically known for its aviation industry and the Caproni aircraft manufacturing facilities.
-
E.
Tilelli
Tilelli is a surname most notably associated with retired U.S. Army General John H. Tilelli Jr.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea4091f48190b5174d7a5cfd2bd8 |
completed | March 31, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce897a958c81909b611fac377e26ca |
completed | April 2, 2026, 3:21 p.m. |
| NEDg | Description generation | batch_69ce8a9df47c81909ba9ef8dff1db7b1 |
completed | April 2, 2026, 3:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce8b48841c8190bcf11aeb25355649 |
completed | April 2, 2026, 3:29 p.m. |
Created at: March 30, 2026, 6:21 p.m.