Triple
T28645966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haya |
E725055
|
entity |
| Predicate | metalworkingProduct |
P165167
|
FINISHED |
| Object | iron tools |
—
|
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: iron tools | Statement: [Haya, metalworkingProduct, iron tools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metalworkingProduct Context triple: [Haya, metalworkingProduct, iron tools]
-
A.
materialMachined
Indicates that one entity is a material that has been shaped, cut, or processed by another entity using a machining operation.
-
B.
mainMetalProduced
Indicates that a location, facility, or process primarily produces a particular metal as its main output.
-
C.
allMetalConstruction
Indicates that something is constructed entirely or almost entirely from metal components.
-
D.
weaponMaterial
Indicates that a weapon is made from, composed of, or primarily constructed using a specified material.
-
E.
weaponForged
Indicates that one entity has been created or shaped as a weapon by another entity through a forging process.
- 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_69f01d8423888190bd2f4e52605bf261 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 4:48 a.m.