Triple
T26803946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danville |
E671174
|
entity |
| Predicate | hasInUniverseLocation |
P120678
|
FINISHED |
| Object | Tri-State Area |
—
|
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: Tri-State Area | Statement: [Danville, hasInUniverseLocation, Tri-State Area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInUniverseLocation Context triple: [Danville, hasInUniverseLocation, Tri-State Area]
-
A.
hasInUniverseLocationRelation
chosen
Indicates a relationship where an entity is associated with, or situated at, a specific location within a fictional or defined universe or setting.
-
B.
inUniverseLocationType
Indicates the type or category of location that something occupies within a fictional or defined universe or setting.
-
C.
builtLocationInUniverse
Indicates that a construction or structure was created or established at a specific location within a particular universe or cosmic setting.
-
D.
residesInFictionalLocation
Indicates that an entity lives or is based in a location that is explicitly fictional or imaginary.
-
E.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
- 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_69eeb31fbd888190a82dac5822e453bc |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: April 27, 2026, 4:25 a.m.