Triple
T23079988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bugis area |
E575440
|
entity |
| Predicate | hasTraditionalVesselType |
P114166
|
FINISHED |
| Object | pinisi ship |
—
|
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: pinisi ship | Statement: [Bugis area, hasTraditionalVesselType, pinisi ship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalVesselType Context triple: [Bugis area, hasTraditionalVesselType, pinisi ship]
-
A.
traditionalVessel
Indicates that one entity is a vessel or container that follows traditional, customary, or historically established forms, designs, or uses in relation to another entity.
-
B.
hasTraditionalBoatType
chosen
Indicates that an entity is associated with or characterized by a specific traditional type of boat.
-
C.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
D.
hasTraditionalFormIn
Indicates that something possesses a customary or historically established form or representation within a specified context, system, or location.
-
E.
hasTraditionalValue
Indicates that something embodies, reflects, or is associated with long-established customs, norms, or cultural values.
- 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_69e245be28d48190ad1348d5a73db37d |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18c66a80481909ebc2ba69f1e4bd9 |
completed | April 29, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:56 p.m.