Triple
T25294218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beichuan Qiang Autonomous County |
E634170
|
entity |
| Predicate | hasReconstructionSupportFrom |
P180289
|
FINISHED |
| Object | central government of China |
—
|
NE NERFINISHED |
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: central government of China | Statement: [Beichuan Qiang Autonomous County, hasReconstructionSupportFrom, central government of China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReconstructionSupportFrom Context triple: [Beichuan Qiang Autonomous County, hasReconstructionSupportFrom, central government of China]
-
A.
hasReconstructionFeature
Indicates that something possesses a characteristic, component, or attribute specifically related to reconstruction.
-
B.
hasReconstructionType
Indicates the specific method or category of reconstruction applied to an object, structure, or dataset.
-
C.
hasReconstructionStandard
Indicates that something is associated with or governed by a specific standard or guideline for how it should be reconstructed.
-
D.
hasReconstructionLevel
Indicates the degree or stage to which something has been rebuilt, restored, or reconstructed.
-
E.
hasReconstructionDomain
Indicates that something is associated with or defined over a particular domain used for reconstruction (e.g., in analysis, modeling, or signal/image reconstruction).
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
| PDg | Predicate description generation | batch_69f73adfd9a081908adae6bd59dfefb9 |
completed | May 3, 2026, 12:09 p.m. |
Created at: April 21, 2026, 1:22 p.m.