Triple
T13148666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twin Bridges |
E312404
|
entity |
| Predicate | hasNumberOfMainAreas |
P63968
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Twin Bridges, hasNumberOfMainAreas, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMainAreas Context triple: [Twin Bridges, hasNumberOfMainAreas, 2]
-
A.
numberOfMainHouses
Indicates the quantity of primary or main residential houses associated with an entity.
-
B.
hasCoreArea
Indicates that an entity possesses a primary or central area that is fundamental to its structure, function, or focus.
-
C.
hasSubstantiveArea
Indicates that one entity is associated with, or falls within, a particular substantive field or domain of activity, knowledge, or regulation.
-
D.
hasNumberOfCentres
chosen
Indicates the relationship specifying how many centers (or central units/locations) are associated with a given entity.
-
E.
numberOfMainCourtyards
Indicates the quantity of primary courtyards associated with an entity.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:11 p.m.