Triple
T16258831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal_Coat_of_Arms_used_in_Belize |
E394699
|
entity |
| Predicate | supportersDepict |
P122391
|
FINISHED |
| Object | two_woodcutters |
—
|
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: two_woodcutters | Statement: [Royal_Coat_of_Arms_used_in_Belize, supportersDepict, two_woodcutters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportersDepict Context triple: [Royal_Coat_of_Arms_used_in_Belize, supportersDepict, two_woodcutters]
-
A.
supporters
Indicates a relationship where one entity backs, endorses, or actively helps another entity, cause, or position.
-
B.
supportersDescription
Indicates that one entity provides support, endorsement, or backing to another entity.
-
C.
supporterOf
Indicates that one entity backs, advocates for, or provides assistance to another entity, cause, or organization.
-
D.
opponentSupporters
Indicates that the related entities are supporters or backers of opposing sides in a contest, conflict, or competition.
-
E.
supporter
Indicates a relationship where one entity backs, advocates for, or provides assistance to another entity, often in an ongoing or affiliative way.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c1fa208190995feaeba766b45f |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:04 a.m.