Triple
T9052490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pac Bo |
E216917
|
entity |
| Predicate | distanceFromCaoBangCity |
P86099
|
FINISHED |
| Object | approximately 50 kilometers |
—
|
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: approximately 50 kilometers | Statement: [Pac Bo, distanceFromCaoBangCity, approximately 50 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromCaoBangCity Context triple: [Pac Bo, distanceFromCaoBangCity, approximately 50 kilometers]
-
A.
distanceFromHanoi
Indicates the spatial distance between a given location and Hanoi.
-
B.
distanceFromCanThoCenter
Indicates the measured spatial distance between a given location and the central point of Can Tho.
-
C.
distanceToDaNang_km
Indicates the distance, measured in kilometers, between a given location and Da Nang.
-
D.
distanceToHoChiMinhCity
Indicates the physical distance between a given location or entity and Ho Chi Minh City.
-
E.
distanceFromSihanoukville
Indicates the measured distance between a given location and Sihanoukville.
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a700de48190aa9f61d850e01cbd |
completed | April 1, 2026, 1:52 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee566b081909e3cdaf551dbd0ec |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f4f1cb48190a025d1b3d8d7a790 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:10 p.m.