Triple
T24048224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TANGO |
E595579
|
entity |
| Predicate | manufacturerHeadquartersLocation |
P91520
|
FINISHED |
| Object | Bussnang, Switzerland |
—
|
NE NERFINISHED |
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: Bussnang, Switzerland | Statement: [TANGO, manufacturerHeadquartersLocation, Bussnang, Switzerland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: manufacturerHeadquartersLocation Context triple: [TANGO, manufacturerHeadquartersLocation, Bussnang, Switzerland]
-
A.
hasManufacturerHeadquartersIn
chosen
Indicates that the location specified is the place where the manufacturer’s main headquarters is situated.
-
B.
headquartersLocationOfBrand
Indicates the place where a brand’s main corporate or administrative headquarters is located.
-
C.
employerHeadquarters
Indicates the location where an employer’s main corporate offices or central administrative operations are based.
-
D.
headquartersLocation
Indicates the place where an organization’s main administrative center or principal office is located.
-
E.
majorCompanyHeadquartered
Indicates that a company is a primary or significant corporate entity whose main headquarters is located in a specified place.
- 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_69e288c06a908190899cad4531f32c9a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9cd50648190b009e97e5be53e8b |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:18 p.m.