Triple
T37576642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detroit television market |
E934838
|
entity |
| Predicate | notableStationCity |
P78960
|
FINISHED |
| Object | Detroit |
E2603
|
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: Detroit | Statement: [Detroit television market, notableStationCity, Detroit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableStationCity Context triple: [Detroit television market, notableStationCity, Detroit]
-
A.
notableTerminusCity
Indicates that a city is notably recognized as a terminus (endpoint) of a route, line, or network.
-
B.
notableCityOfOperation
Indicates that a city is a primary or particularly significant location where an entity conducts its operations or activities.
-
C.
notableCityIncluded
Indicates that a notable or significant city is contained within, or is part of, a larger geographic or administrative entity.
-
D.
hasStationInCity
chosen
Indicates that a station or facility is located within a particular city.
-
E.
notableCitiesRepresented
Indicates that an entity includes or features certain cities as particularly important or prominently represented within it.
- 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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40ba3fc6d081908c7e27291546dc9e |
completed | June 28, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.