Triple
T97178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Triangle (universities) |
E1957
|
entity |
| Predicate | hasInformalStatus |
P4154
|
FINISHED |
| Object | not a legally defined consortium |
—
|
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: not a legally defined consortium | Statement: [Golden Triangle (universities), hasInformalStatus, not a legally defined consortium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInformalStatus Context triple: [Golden Triangle (universities), hasInformalStatus, not a legally defined consortium]
-
A.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
B.
hasUNStatus
Indicates that an entity holds a particular formal status or recognition within the United Nations system.
-
C.
hasIconicStatus
Indicates that an entity holds a widely recognized, emblematic, or culturally significant status within a particular domain or context.
-
D.
status
Indicates the current condition, state, or standing of an entity within a given context.
-
E.
electoralStatus
Indicates the current state or condition of an entity in relation to an election process (e.g., running, elected, defeated, or not a candidate).
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a250ca7eec8190b31f7e61f5e3ee1f |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.