Triple
T38029735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippine Presidential Unit Citation |
E948873
|
entity |
| Predicate | wearBy |
P271
|
FINISHED |
| Object | individual members of cited units |
—
|
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: individual members of cited units | Statement: [Philippine Presidential Unit Citation, wearBy, individual members of cited units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearBy Context triple: [Philippine Presidential Unit Citation, wearBy, individual members of cited units]
-
A.
wearIndicates
Indicates that one entity is wearing or has clothing or an accessory on its body, typically as a visible or functional item.
-
B.
wearClassification
Indicates a classification relationship specifying the type or category of wear associated with an entity or interaction.
-
C.
wears
chosen
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
D.
areWornOn
Indicates that one entity is typically placed on and carried by another entity as an item of clothing or accessory.
-
E.
wearLocation
Indicates the typical body part or location on which an item is worn.
- 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc999ba0081908ec76b8a771bf071 |
completed | May 6, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.