Triple
T28750676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuanku Abdul Rahman University College |
E731515
|
entity |
| Predicate | hasNameInSomeUTARContexts |
P34621
|
FINISHED |
| Object | UTAR campus |
—
|
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: UTAR campus | Statement: [Tuanku Abdul Rahman University College, hasNameInSomeUTARContexts, UTAR campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInSomeUTARContexts Context triple: [Tuanku Abdul Rahman University College, hasNameInSomeUTARContexts, UTAR campus]
-
A.
hasNameDayContext
Indicates that an entity’s name day is interpreted or celebrated within a specific contextual framework (such as culture, calendar system, or tradition).
-
B.
namedInContextOf
chosen
Indicates that an entity is mentioned or identified specifically within a particular context, situation, or frame of reference.
-
C.
hasNameInInnu
Indicates that an entity is known by a specific name expressed in the Innu language.
-
D.
usesNameForm
Indicates that one entity adopts or applies a particular standardized form or variant of a name associated with another entity.
-
E.
hasUnicodeName
Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
- 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_69f043ed68a881909e858a06bab7a247 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: April 28, 2026, 6:07 a.m.