Triple
T15584453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trumbo |
E374580
|
entity |
| Predicate | characterPortrayed |
P1507
|
FINISHED |
| Object | Hedda Hopper |
E457009
|
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: Hedda Hopper | Statement: [Trumbo, characterPortrayed, Hedda Hopper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hedda Hopper Context triple: [Trumbo, characterPortrayed, Hedda Hopper]
-
A.
Hedda Hopper
chosen
Hedda Hopper was a prominent American gossip columnist and former actress, notorious for her influential and often fearsome Hollywood gossip column during the mid-20th century.
-
B.
Louella Parsons
Louella Parsons was a powerful American gossip columnist and film critic who became one of early Hollywood’s most influential media figures.
-
C.
Dorothy Kilgallen
Dorothy Kilgallen was an American journalist and television personality best known as a sharp-witted newspaper columnist and longtime panelist on the game show "What's My Line?".
-
D.
Marguerite Lauer
Marguerite Lauer was the wife of renowned French Egyptologist Jean-Philippe Lauer.
-
E.
Louella
Louella is a feminine given name of English origin, often considered a combination of "Louise" and "Ella."
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e47971481909e986dd999354628 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4f71e48190a15eb0a2138f083f |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:11 a.m.