Triple
T15824350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dennis Cooper (The Texas Chainsaw Massacre 2003) |
E383697
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Kemper |
E535337
|
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: Kemper | Statement: [Dennis Cooper (The Texas Chainsaw Massacre 2003), associatedWithCharacter, Kemper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kemper Context triple: [Dennis Cooper (The Texas Chainsaw Massacre 2003), associatedWithCharacter, Kemper]
-
A.
Kemper
chosen
Kemper is a surname most prominently associated with the American banking and philanthropic family involved in finance, arts, and education.
-
B.
Kempner
Kempner is a surname most notably associated with Karen Kempner Zuckerberg, the mother of Facebook co-founder Mark Zuckerberg.
-
C.
Ebersole
Ebersole is a surname most notably associated with American actress and singer Christine Ebersole.
-
D.
Seiberling
Seiberling is a surname most notably associated with American industrialist Frank Seiberling, co-founder of the Goodyear Tire & Rubber Company.
-
E.
Kashmore
Kashmore is a town in Pakistan’s Sindh province that serves as a regional hub near the Guddu Barrage on the Indus River.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e5f46748190acb46cc482501307 |
completed | April 16, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff999bba548190a39adc2d0e11c605 |
completed | May 9, 2026, 8:31 p.m. |
Created at: April 10, 2026, 4:49 a.m.