Triple
T1435089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smith |
E30542
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Smythe |
E163515
|
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: Smythe | Statement: [Smith, hasVariant, Smythe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smythe Context triple: [Smith, hasVariant, Smythe]
-
A.
Smyth
chosen
Smyth is a less common variant spelling of the surname Smith, found primarily in English-speaking countries.
-
B.
McCauley
McCauley is the maiden surname of Rosa Parks, the prominent American civil rights activist known for her pivotal role in the Montgomery bus boycott.
-
C.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
D.
Hoyte
Hoyte is the first name of Hoyte van Hoytema, a renowned Dutch-Swedish cinematographer known for his work on major films such as "Interstellar" and "Dunkirk."
-
E.
Keefer
Keefer was a distinguished racing greyhound renowned for its achievements on the track, earning induction into the Greyhound Hall of Fame.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c50250b88190a0fcf3e0cbba0b1a |
completed | March 1, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08b5ba94819092e66e8dfd6bf87d |
completed | March 8, 2026, 5:27 a.m. |
Created at: March 1, 2026, 8 p.m.