Triple
T9906448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Daley |
E185023
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Daley |
E131649
|
NE FINISHED |
How this triple was built (2 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: Daley | Statement: [Tom Daley, familyName, Daley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daley Context triple: [Tom Daley, familyName, Daley]
-
A.
Daley
chosen
Daley is a prominent American political surname most famously associated with the longtime Chicago mayoral family.
-
B.
Dolan
Dolan is a surname most prominently associated with the American business family that controls Madison Square Garden Sports and Entertainment, including executive James L. Dolan.
-
C.
Willis
Willis is a masculine given name and surname of English origin, often considered a variant or cognate of the name Wilson.
-
D.
Durbin
Durbin is a small town in Pocahontas County, West Virginia, known for its scenic location in the Allegheny Mountains and its historic excursion railroad.
-
E.
Durbin
Durbin is a popular Bengali novel by acclaimed Indian writer Shirshendu Mukhopadhyay, known for its blend of psychological depth and engaging storytelling.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb50cf8808190a41e565216712704 |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb316a188190a1c7fbe0d1997cf5 |
completed | April 5, 2026, 4:55 a.m. |
Created at: March 30, 2026, 8:40 p.m.