Triple
T28075962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhuge clan |
E709541
|
entity |
| Predicate | hasFictionalDepictions |
P191964
|
FINISHED |
| Object | Romance of the Three Kingdoms |
—
|
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: Romance of the Three Kingdoms | Statement: [Zhuge clan, hasFictionalDepictions, Romance of the Three Kingdoms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalDepictions Context triple: [Zhuge clan, hasFictionalDepictions, Romance of the Three Kingdoms]
-
A.
hasRealityCounterpartInFiction
Indicates that a fictional element corresponds to or is based on a real-world counterpart within a work of fiction.
-
B.
hasSpeciesInFiction
Indicates that a fictional work or universe features a particular species as part of its narrative or setting.
-
C.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
- F. None of above. chosen
Provenance (4 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_69ef9b6f8078819098b741274cd1a2ee |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
| PDg | Predicate description generation | batch_69fcf1b241888190a243f07051c71383 |
completed | May 7, 2026, 8:10 p.m. |
Created at: April 27, 2026, 8:49 p.m.