Triple
T33887107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanger Outlets |
E868659
|
entity |
| Predicate | numberOfCenters |
P63968
|
FINISHED |
| Object | more than 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: more than 30 | Statement: [Tanger Outlets, numberOfCenters, more than 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCenters Context triple: [Tanger Outlets, numberOfCenters, more than 30]
-
A.
hasNumberOfCentres
chosen
Indicates the relationship specifying how many centers (or central units/locations) are associated with a given entity.
-
B.
numberOfDistributionCenters
Indicates the quantity of distribution centers associated with a given entity.
-
C.
urbanCentersCount
Indicates the number of urban centers associated with or contained within a given entity.
-
D.
numberOfResearchCentres
Indicates the quantity of research centres associated with a given entity.
-
E.
numberOfDrillingCenters
Indicates the quantity of drilling centers associated with or involved in a given entity or context.
- 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_69f34996761c8190864e42f7c9cf215b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a035ead9ee0819099806d2670dc9c50 |
completed | May 12, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_6a035dc9210c8190a9044c6a53211520 |
completed | May 12, 2026, 5:05 p.m. |
Created at: May 1, 2026, 1:48 a.m.