Triple
T25629492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple II |
E642532
|
entity |
| Predicate | oppositeStructure |
P114339
|
FINISHED |
| Object | Temple I |
—
|
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: Temple I | Statement: [Temple II, oppositeStructure, Temple I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oppositeStructure Context triple: [Temple II, oppositeStructure, Temple I]
-
A.
hasOppositeStructure
chosen
Indicates that one entity possesses a structure that is the inverse or opposite in form, arrangement, or organization relative to another entity.
-
B.
opposite
Indicates that one entity is positioned or oriented directly across from, or in a contrary or reverse relation to, another entity.
-
C.
hasConceptualOpposite
Indicates that one entity represents a concept that is fundamentally opposed or contrary in meaning to the concept represented by another entity.
-
D.
opposedOperation
Indicates that one operation is in conflict with, counters, or works against another operation.
-
E.
usedStructure
Indicates that one entity makes use of, relies on, or operates through a particular structure (physical, logical, or organizational) to perform its function or action.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 21, 2026, 5:17 p.m.