Triple
T772274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detroit Three |
E16306
|
entity |
| Predicate | hasMemberHeadquartersCity |
P19000
|
FINISHED |
| Object | Detroit (historically for all three) |
—
|
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: Detroit (historically for all three) | Statement: [Detroit Three, hasMemberHeadquartersCity, Detroit (historically for all three)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberHeadquartersCity Context triple: [Detroit Three, hasMemberHeadquartersCity, Detroit (historically for all three)]
-
A.
hasHeadquartersType
Indicates the specific kind or classification of headquarters associated with an entity.
-
B.
hasParentCompanyHeadquarters
Indicates that a company’s parent organization has its main headquarters located at a specified place.
-
C.
continentHeadquarters
Indicates that an entity’s main headquarters is located on a specified continent.
-
D.
isGlobalCityFor
Indicates that a city holds significant global importance or influence for a specified country, region, or domain (e.g., economy, culture, or politics).
-
E.
hasFamousCity
Indicates that an entity possesses or is associated with a city that is widely recognized or renowned.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a706abf88190a1cbc2dfbbf9968a |
completed | March 1, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69a4a508c42c8190850a0ac7844a3ea9 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a5a35c68819082429755c046e9a7 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:37 p.m.