Triple
T4284720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claire |
E97238
|
entity |
| Predicate | variant |
P4680
|
FINISHED |
| Object | Clare |
unclear NED1
|
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: Clare | Statement: [Claire, variant, Clare]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clare Context triple: [Claire, variant, Clare]
-
A.
Clare
Clare is a historic market town and civil parish in Suffolk, England, known for its medieval architecture and picturesque countryside setting.
-
B.
Clare
Clare is a central character in the Restoration comedy "The Witty Fair One," known for embodying the play’s themes of wit, romance, and social intrigue.
-
C.
Clare
Clare is a small town in South Australia that serves as the main service and tourism hub for the surrounding Clare Valley wine region.
-
D.
Clarey
Clarey is a diminutive or affectionate form of the given name Clara.
-
E.
Clare West
Clare West was an early Hollywood costume designer known for her influential work on major silent films, including collaborations with director Cecil B. DeMille.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3503c062c81908f9a9eeab5381ec9 |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7c2023c8190a2359f8cabcecd2c |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:07 p.m.