Triple
T7856959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wah Campus |
E182400
|
entity |
| Predicate | regionServed |
P82
|
FINISHED |
| Object | Wah |
E700846
|
NE 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: Wah | Statement: [Wah Campus, regionServed, Wah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wah Context triple: [Wah Campus, regionServed, Wah]
-
A.
Wah
chosen
Wah is a city in Pakistan’s Punjab province, known for its industrial significance and proximity to major military and educational institutions.
-
B.
WOAH
WOAH is the acronym for the World Organisation for Animal Health, an intergovernmental body that sets international standards for animal health and welfare.
-
C.
Woah
"Woah" is a popular hip-hop single by American rapper Lil Baby known for its catchy hook and viral dance.
-
D.
Waah!
"Waah!" is a popular hit song by Tanzanian artist Diamond Platnumz, known for its catchy Afro-pop sound and widespread success across East Africa and beyond.
-
E.
Wa
Wa is a town in northwestern Ghana that serves as an administrative, commercial, and cultural hub for the surrounding region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82887fd48190975896bf38c4596b |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a75de548190af5653409a3b3881 |
completed | March 31, 2026, 12:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdf3828fc81908a118420a6b0a736 |
completed | March 31, 2026, 2:50 p.m. |
Created at: March 30, 2026, 4:52 p.m.