Triple
T14467201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King John’s Castle |
E358743
|
entity |
| Predicate | battlementType |
P101353
|
FINISHED |
| Object | crenellated walls |
—
|
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: crenellated walls | Statement: [King John’s Castle, battlementType, crenellated walls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battlementType Context triple: [King John’s Castle, battlementType, crenellated walls]
-
A.
battlementFeature
chosen
Indicates that one architectural element functions as a defensive battlement or is a structural feature of a battlement.
-
B.
fortType
Indicates the specific kind or classification of a fort associated with an entity.
-
C.
materialOfFortifications
Indicates that a specified material is used in the construction or composition of certain fortifications.
-
D.
castleBuiltOf
Indicates that a castle is constructed primarily from a specified material.
-
E.
garrisonType
Indicates the specific kind or classification of military garrison associated with an 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f8613c819080424104c0b7f4c3 |
completed | April 14, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.