Triple
T10475920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camino de Santiago |
E247043
|
entity |
| Predicate | hasAssociatedHeadgear |
P31655
|
FINISHED |
| Object | broad-brimmed hat |
—
|
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: broad-brimmed hat | Statement: [Camino de Santiago, hasAssociatedHeadgear, broad-brimmed hat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedHeadgear Context triple: [Camino de Santiago, hasAssociatedHeadgear, broad-brimmed hat]
-
A.
associatedWithHeadgear
chosen
Indicates a relationship where an entity is connected or related to a particular item of headgear, such as by wearing, using, or being characterized by it.
-
B.
authorizedHeadgear
Indicates that a particular item of headgear is officially permitted or approved for use in a given context or by a specific authority.
-
C.
helmetNumber
Indicates the identifying number assigned to a person or object as displayed on their helmet.
-
D.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
E.
helmetColor
Indicates the specific color attribute assigned to a helmet in the relationship.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094f6b408190a5a26b1a82e4a02b |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:21 p.m.