Triple
T8885245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vice Principal Douglas Panch |
E211512
|
entity |
| Predicate | relationshipToEvent |
P85529
|
FINISHED |
| Object | official pronouncer |
—
|
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: official pronouncer | Statement: [Vice Principal Douglas Panch, relationshipToEvent, official pronouncer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEvent Context triple: [Vice Principal Douglas Panch, relationshipToEvent, official pronouncer]
-
A.
relationshipStartEvent
Indicates the event or point in time at which a particular relationship between entities begins.
-
B.
associatedWithCorporateEvent
Indicates that an entity has a connection or involvement with a specific corporate event.
-
C.
relationshipWithGuests
Indicates the nature or status of the connection or interaction that someone has with their guests.
-
D.
associatedEventType
Indicates that one entity is linked to another by the type or category of event with which it is associated.
-
E.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc616cf8c48190a27b381e48f23377 |
completed | April 1, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5d6e54808190af4156edd4c8ffbc |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 6:53 p.m.