Triple
T14967754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Minister House Karachi |
E373234
|
entity |
| Predicate | locatedInCityType |
P66935
|
FINISHED |
| Object | metropolis |
—
|
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: metropolis | Statement: [Chief Minister House Karachi, locatedInCityType, metropolis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCityType Context triple: [Chief Minister House Karachi, locatedInCityType, metropolis]
-
A.
basedInCity
Indicates that an entity has its primary location, headquarters, or main operations situated in a specified city.
-
B.
locatedInUrbanizationType
chosen
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
C.
housedInCity
Indicates that one entity (such as a building, organization, or facility) is located within and contained by a particular city.
-
D.
cityLocatedIn
Indicates that a city is geographically situated within a specified larger administrative or territorial region.
-
E.
locatedInCapitalCityPort
Indicates that something is situated within the port area of a country's capital city.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e44cb0819096e09f8026ef8174 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:48 a.m.