Triple
T16746458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Father Theobald Mathew statue |
E406967
|
entity |
| Predicate | isUrbanLandmark |
P124480
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Father Theobald Mathew statue, isUrbanLandmark, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanLandmark Context triple: [Father Theobald Mathew statue, isUrbanLandmark, yes]
-
A.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
-
B.
isUrbanSectionOf
Indicates that one area or segment is the part of a larger entity that lies within an urban or city environment.
-
C.
isUrbanPark
Indicates that a location is designated and used as a public park within an urban or metropolitan area.
-
D.
isDowntownLandmark
Indicates that a location is recognized as a notable or prominent landmark within a city’s downtown area.
-
E.
partOfSkylineOf
Indicates that one entity is a visible component or feature contributing to the overall skyline profile of another entity, typically a city or urban area.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa2311748190a17416de577ad159 |
completed | April 18, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:21 a.m.