Triple
T34121318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Tut (Batman 1960s TV series) |
E875141
|
entity |
| Predicate | fictionalCityOfActivity |
P48498
|
FINISHED |
| Object | Gotham City |
—
|
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: Gotham City | Statement: [King Tut (Batman 1960s TV series), fictionalCityOfActivity, Gotham City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCityOfActivity Context triple: [King Tut (Batman 1960s TV series), fictionalCityOfActivity, Gotham City]
-
A.
cityOfFictionalActivity
chosen
Indicates that a fictional activity, event, or storyline takes place in the specified city.
-
B.
fictionalCitySetting
Indicates that a narrative, event, or work is set in a city that is imaginary or does not exist in the real world.
-
C.
fictionalCityServed
Indicates that a fictional city is served by a particular service, facility, or infrastructure (such as transport, utilities, or institutions).
-
D.
partOfFictionalCity
Indicates that one entity is a component, area, or subdivision within a larger fictional city.
-
E.
fictionalCapital
Indicates that a location serves as the capital city within a fictional or imaginary political or geographic entity.
- 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_69f349a9271c81909576994c9ef7b179 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69feb5e66224819083b87c3707a5a5e0 |
completed | May 9, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69feb3bd700c8190991ed200cd3c04db |
completed | May 9, 2026, 4:10 a.m. |
Created at: May 1, 2026, 1:53 a.m.