Triple
T23683494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | splurge gun |
E585097
|
entity |
| Predicate | materialFired |
P153370
|
FINISHED |
| Object | custard |
—
|
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: custard | Statement: [splurge gun, materialFired, custard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialFired Context triple: [splurge gun, materialFired, custard]
-
A.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
B.
fireTowerMaterial
Indicates the material from which a fire tower is constructed or primarily made.
-
C.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
D.
materialInvolved
Indicates that a particular material participates in, is used by, or is otherwise involved in the referenced process, event, or relationship.
-
E.
materialMelted
Indicates that a material has undergone melting, transitioning from a solid to a liquid state.
- 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4fa72b48190b872670b6546a718 |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f157cc43a881909ed2d8b0a09b5d73 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 17, 2026, 6:51 p.m.