Triple
T35118495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Maiden |
E1014105
|
entity |
| Predicate | cultCenterInFiction |
P182544
|
FINISHED |
| Object | Great Sept of Baelor |
—
|
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: Great Sept of Baelor | Statement: [the Maiden, cultCenterInFiction, Great Sept of Baelor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cultCenterInFiction Context triple: [the Maiden, cultCenterInFiction, Great Sept of Baelor]
-
A.
cultureInFiction
Indicates that a work of fiction features, represents, or is thematically centered on a particular culture.
-
B.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or narrative context.
-
C.
basedInFictionalSetting
Indicates that an entity’s primary location or setting exists within a fictional or imaginary world rather than the real world.
-
D.
targetInFiction
Indicates that one entity is the target or subject of an action, focus, or effect within a fictional work or narrative context.
-
E.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
- 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78dbf72648190a4971a558e9d1889 |
completed | May 3, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78ce43094819093857fc99f269afe |
completed | May 3, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:01 p.m.