Triple
T23569248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The High Place |
E580055
|
entity |
| Predicate | hasFictionalProvince |
P136812
|
FINISHED |
| Object | Poictesme |
—
|
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: Poictesme | Statement: [The High Place, hasFictionalProvince, Poictesme]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalProvince Context triple: [The High Place, hasFictionalProvince, Poictesme]
-
A.
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.
-
B.
hasFictionalCounty
Indicates that one entity includes, is set in, or is associated with a county that is fictional rather than real.
-
C.
belongsToFictionalRegion
chosen
Indicates that an entity is located within, associated with, or under the jurisdiction of a fictional or imaginary geographic region.
-
D.
fictionalGeographicRegion
Indicates that a geographic region exists only in fiction or imagination rather than in the real world.
-
E.
hasBranchInFictionalLocation
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
- 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_69e24601a9108190bc31e83833c980e4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1afd15ca48190afd119ec1b4a07b2 |
completed | April 29, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69f118bcc0b08190b25a8dddfd461a0e |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:35 p.m.