Triple
T36315813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Sant Felip Neri |
E894187
|
entity |
| Predicate | hasFaçadeDamageFrom |
P992
|
FINISHED |
| Object | Spanish Civil War |
—
|
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: Spanish Civil War | Statement: [Church of Sant Felip Neri, hasFaçadeDamageFrom, Spanish Civil War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFaçadeDamageFrom Context triple: [Church of Sant Felip Neri, hasFaçadeDamageFrom, Spanish Civil War]
-
A.
hasTypeOfDamage
Indicates that an entity experiences or exhibits a specific kind or category of damage.
-
B.
sufferedDamageTo
Indicates that one entity has experienced harm, loss, or deterioration affecting another entity or one of its parts.
-
C.
hasDam
Indicates that a watercourse, reservoir, or similar feature is impounded or controlled by a specific dam.
-
D.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
E.
damagedIn
chosen
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
- 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_69f76e4d1a788190a6ab6ccca28547a7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe6b7c785c8190aaab06019f571434 |
completed | May 8, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fe68edef20819081c77f9607b944dd |
completed | May 8, 2026, 10:51 p.m. |
Created at: May 3, 2026, 4:09 p.m.