Triple
T1274177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barracks Row |
E15774
|
entity |
| Predicate | hasStreetscapeFeatures |
P24448
|
FINISHED |
| Object | historic row buildings |
—
|
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: historic row buildings | Statement: [Barracks Row, hasStreetscapeFeatures, historic row buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetscapeFeatures Context triple: [Barracks Row, hasStreetscapeFeatures, historic row buildings]
-
A.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
B.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
-
C.
hasPedestrianPlazaOn
Indicates that a pedestrian plaza is located on, or directly associated with, a specified surface, structure, or area.
-
D.
hasStreetEnvironment
chosen
Indicates that an entity is associated with or characterized by a particular type or quality of street-level surroundings or conditions.
-
E.
hasNotableStreet
Indicates that an entity is associated with a particular street that is considered notable or significant.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.