Triple
T38463682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chengdu Hunters |
E912511
|
entity |
| Predicate | locationLicense |
P102819
|
FINISHED |
| Object | Chengdu, China |
E280635
|
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: Chengdu, China | Statement: [Chengdu Hunters, locationLicense, Chengdu, China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationLicense Context triple: [Chengdu Hunters, locationLicense, Chengdu, China]
-
A.
cityOfLicense
Indicates the city in which an entity (typically a broadcast station or similar regulated service) is officially licensed or authorized to operate.
-
B.
vehicleRegistrationLocation
Indicates the place or jurisdiction where a vehicle is officially registered.
-
C.
licensePlateLocation
Indicates the physical position or placement of a license plate on or relative to an object or vehicle.
-
D.
stateOfLicense
Indicates the jurisdiction or state that has issued or governs the relevant license.
-
E.
countryOfLicence
chosen
Indicates the country that has issued or granted a particular licence.
- F. None of above.
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_69f76e861d8c81908559031dc66e3c15 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41d647e62081909378907c0f44287d |
completed | June 29, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.