Triple
T11156870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erin Hannon |
E263931
|
entity |
| Predicate | becomesMainCharacterIn |
P32529
|
FINISHED |
| Object | later seasons of The Office (U.S.) |
—
|
LITERAL 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: later seasons of The Office (U.S.) | Statement: [Erin Hannon, becomesMainCharacterIn, later seasons of The Office (U.S.)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becomesMainCharacterIn Context triple: [Erin Hannon, becomesMainCharacterIn, later seasons of The Office (U.S.)]
-
A.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
B.
protagonistIs
chosen
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
C.
mainCharactersAre
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
D.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
E.
hasMainThemeCharacter
Indicates that a work (such as a story, film, or game) features a specific character as its central or primary thematic focus.
- F. None of above.
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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8741cd48190b7cc29c6b6bc54ff |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cec26fc8190a5497d186306f935 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.