Triple
T31999400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shane’s Castle |
E817081
|
entity |
| Predicate | hasRuinedSection |
P32402
|
FINISHED |
| Object | main castle |
—
|
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: main castle | Statement: [Shane’s Castle, hasRuinedSection, main castle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuinedSection Context triple: [Shane’s Castle, hasRuinedSection, main castle]
-
A.
hasRuin
chosen
Indicates that one entity possesses, contains, or is associated with a ruin or ruined structure.
-
B.
hasSectionInvolved
Indicates that a particular section or subdivision is involved or participates in a specified relationship, process, or context.
-
C.
rupturedSegmentOf
Indicates that one entity is a segment that has undergone rupture and is part of, or derived from, another entity.
-
D.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
E.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
- 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_69f348f8ce388190ae84376b1f348f12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 12:14 a.m.