Triple
T16624899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krimzon Guard fortress |
E403919
|
entity |
| Predicate | inUniverseCitySection |
P80700
|
FINISHED |
| Object | central Haven City |
—
|
LITERAL FINISHED |
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: central Haven City | Statement: [Krimzon Guard fortress, inUniverseCitySection, central Haven City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inUniverseCitySection Context triple: [Krimzon Guard fortress, inUniverseCitySection, central Haven City]
-
A.
inUniverse
Indicates that one entity exists, occurs, or is set within the fictional or conceptual universe defined by another entity.
-
B.
isUrbanSectionOf
chosen
Indicates that one area or segment is the part of a larger entity that lies within an urban or city environment.
-
C.
inUniverseLocationType
Indicates the type or category of location that something occupies within a fictional or defined universe or setting.
-
D.
inUniverseType
Indicates that one entity exists within, or is categorized as belonging to, a particular fictional or conceptual universe type defined by the other entity.
-
E.
isUNCity
Indicates that a city is officially recognized as hosting one or more United Nations offices, agencies, or headquarters.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37551cd888190becc21deba87980d |
completed | April 18, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.