Triple
T24022664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Match |
E594866
|
entity |
| Predicate | leadCharacterSecondaryOccupation |
P154900
|
FINISHED |
| Object | matchmaker |
—
|
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: matchmaker | Statement: [Miss Match, leadCharacterSecondaryOccupation, matchmaker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterSecondaryOccupation Context triple: [Miss Match, leadCharacterSecondaryOccupation, matchmaker]
-
A.
hasSecondaryProtagonistOccupation
Indicates that a secondary protagonist in a narrative has a specific occupation or job role.
-
B.
hasOccupationOfDeuteragonist
Indicates that an entity holds the role of deuteragonist, i.e., the second most important character in a narrative or dramatic work.
-
C.
laterPrimaryRole
Indicates that an entity assumes a specified primary role at a later time than another role or state in a sequence.
-
D.
secondaryProtagonistType
Indicates the role or category of a work’s secondary main character in relation to the primary protagonist.
-
E.
hasCoProtagonistOccupation
Indicates that two or more co-protagonists share a specified occupation or professional role.
- F. None of above. chosen
Provenance (4 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_69e288be2c288190a3a46006945557f7 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d7667ff08190bfd14aa4eb776f21 |
completed | April 29, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 9:52 p.m.