Triple
T33887109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanger Outlets |
E868659
|
entity |
| Predicate | hasLocationInCountry |
P195019
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Tanger Outlets, hasLocationInCountry, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocationInCountry Context triple: [Tanger Outlets, hasLocationInCountry, United States]
-
A.
representsLocationInCountry
Indicates that one entity is located within the geographical boundaries of a specified country.
-
B.
subjectLocationCountry
chosen
Indicates that the subject is located within, or associated with, a specific country.
-
C.
meetsInCountry
Indicates that two or more entities have an in-person meeting that takes place within the specified country.
-
D.
locatedInCurrentCountry
Indicates that an entity is situated within the geographic boundaries of the country in which it is presently found.
-
E.
hasCountry
Indicates that one entity possesses, is associated with, or is located within a specific country.
- 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_69feb342994081909481ec8ec5d44928 |
completed | May 9, 2026, 4:08 a.m. |
| PD | Predicate disambiguation | batch_69feb046e4e48190b96649aa28529cc9 |
completed | May 9, 2026, 3:55 a.m. |
Created at: May 1, 2026, 1:48 a.m.