Triple
T5899962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will Clark |
E131196
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Clark |
E119775
|
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: Clark | Statement: [Will Clark, familyName, Clark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clark Context triple: [Will Clark, familyName, Clark]
-
A.
Clark
Clark is the middle name of Herbert Hoover, the 31st president of the United States.
-
B.
Clark
chosen
Clark is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
-
C.
Clayton
Clayton is a district in east Manchester, England, known for its residential character and proximity to the city’s industrial and sporting landmarks.
-
D.
Clayton
Clayton is a town in Johnston County, North Carolina, known as a growing suburban community within the Raleigh metropolitan area.
-
E.
Clayton
Clayton is a common English-language surname borne by numerous notable individuals across fields such as music, sports, politics, and academia.
- 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_69c0085864a88190a569c05ff7d65f29 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0373320cc8190bfdb2b09236f55a5 |
completed | March 22, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c0076cd88190b10e51c52dcc6a2e |
completed | March 23, 2026, 4:22 a.m. |
Created at: March 22, 2026, 3:58 p.m.