Triple
T27148585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capitol View Corridors in Austin, Texas |
E682319
|
entity |
| Predicate | hasNumberOfCorridors |
P4095
|
FINISHED |
| Object | over 30 |
—
|
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: over 30 | Statement: [Capitol View Corridors in Austin, Texas, hasNumberOfCorridors, over 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfCorridors Context triple: [Capitol View Corridors in Austin, Texas, hasNumberOfCorridors, over 30]
-
A.
numberOfCorridors
chosen
Indicates the total count of corridors associated with or contained within a given entity or structure.
-
B.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
C.
lengthOfCorridors
Indicates the measured extent or distance of corridors within a given space or structure.
-
D.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
-
E.
corridorNumber
Indicates the specific corridor identifier or number associated with a location or entity within a building or structured layout.
- 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
Created at: April 27, 2026, 9:12 a.m.