Triple
T5746920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cobweb |
E126757
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Harold F. Kress |
E155211
|
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: Harold F. Kress | Statement: [The Cobweb, editor, Harold F. Kress]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harold F. Kress Context triple: [The Cobweb, editor, Harold F. Kress]
-
A.
Harold F. Kress
chosen
Harold F. Kress was an American film editor renowned for his work on numerous classic Hollywood films and for winning multiple Academy Awards for Best Film Editing.
-
B.
Harold M. Shaw
Harold M. Shaw was an early American film director and actor known for his pioneering work in silent cinema during the 1910s.
-
C.
Harold C. Mayer
Harold C. Mayer was an American financier best known as one of the co-founders of the investment bank Bear Stearns.
-
D.
Frank Seiberling
Frank Seiberling was an American industrialist best known for founding the Goodyear Tire & Rubber Company, which became one of the world’s leading tire manufacturers.
-
E.
Edward M. Kern
Edward M. Kern was a 19th-century American topographer and explorer after whom California’s Kern County was named.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02885b0288190835809681a364b1f |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097fcba40819097543d151b890788 |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:48 p.m.