Triple
T5767435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TREX |
E127248
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | James Clark |
E30299
|
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: James Clark | Statement: [TREX, creator, James Clark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Clark Context triple: [TREX, creator, James Clark]
-
A.
James Clark
chosen
James Clark is a notable figure in the web and technology community recognized for his significant contributions to open standards and digital publishing.
-
B.
James Clark
James Clark was an early settler and prominent figure in Texas history after whom the city of Clarksville, Texas, was named.
-
C.
J. P. Clark
J. P. Clark was a prominent Nigerian poet and playwright, regarded as one of the leading figures of modern African literature.
-
D.
Charles Clark
Charles Clark is a relatively common personal name shared by multiple notable individuals across fields such as politics, sports, and the arts.
-
E.
Les Clark
Les Clark was an American animator and one of Disney’s famed "Nine Old Men," known for his influential work on many classic Disney films.
- 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029731adc8190888adc8178a08e90 |
completed | March 22, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e5d8c8c819081067de808ac1b56 |
completed | March 22, 2026, 11:42 p.m. |
Created at: March 22, 2026, 3:49 p.m.