Triple
T26403294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Conovan |
E663760
|
entity |
| Predicate | numberOfTitularProtagonistsInWork |
P29044
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Mike Conovan, numberOfTitularProtagonistsInWork, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTitularProtagonistsInWork Context triple: [Mike Conovan, numberOfTitularProtagonistsInWork, 2]
-
A.
protagonistCount
chosen
Indicates the number of primary protagonists involved in a given narrative or work.
-
B.
numberOfHumanProtagonists
Indicates the count of human characters that serve as protagonists in a given work or context.
-
C.
numberOfHumanCharacters
Indicates the count of distinct human characters associated with a given entity or context.
-
D.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
E.
numberOfNarrators
Indicates the quantity of distinct narrators associated with a given work or narrative.
- 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_69ee883931888190901be96d75ee23cc |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: April 26, 2026, 11:33 p.m.