Triple
T14120400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ron Clements |
E339889
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Clements |
E747797
|
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: Clements | Statement: [Ron Clements, familyName, Clements]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clements Context triple: [Ron Clements, familyName, Clements]
-
A.
Clements
chosen
Clements is a surname most notably associated with American plant ecologist Frederic Clements, a pioneer in the study of ecological succession.
-
B.
Clem
Clem is a short, informal given name typically used as a diminutive of Clement.
-
C.
Hichens
Hichens is an English surname most notably associated with figures such as novelist Robert Hichens.
-
D.
Mathieson
Mathieson is a surname of Scottish origin, typically regarded as a variant of Matheson and derived from a patronymic meaning “son of Matthew.”
-
E.
Cressner
Cressner is the sadistic, wealthy gambler and primary villain in Stephen King’s short story “The Ledge,” known for forcing a man to risk his life by walking around a narrow ledge high above the city.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de60942a588190beff0058a92f7051 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0641008190b88efacc02ba5314 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.