Triple
T1274185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barracks Row |
E15774
|
entity |
| Predicate | hasPedestrianCharacter |
P28273
|
FINISHED |
| Object | pedestrian-friendly |
—
|
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: pedestrian-friendly | Statement: [Barracks Row, hasPedestrianCharacter, pedestrian-friendly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPedestrianCharacter Context triple: [Barracks Row, hasPedestrianCharacter, pedestrian-friendly]
-
A.
hasPedestrianArea
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
-
B.
hasPedestrianPhase
Indicates that a traffic signal includes a dedicated phase during which pedestrians are allowed to cross.
-
C.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
D.
hasPedestrianTrafficLevel
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
E.
hasPedestrianSignalPattern
Indicates that there is a specific configuration or sequence of pedestrian traffic signals associated with an entity.
- 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_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. |
| PDg | Predicate description generation | batch_69a4c31400c08190a07ccb736df3bf54 |
completed | March 1, 2026, 10:52 p.m. |
Created at: March 1, 2026, 7:50 p.m.