Triple
T34759147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zara |
E1002015
|
entity |
| Predicate | wasSiegeLocationIn |
P92602
|
FINISHED |
| Object | Fourth Crusade |
—
|
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: Fourth Crusade | Statement: [Zara, wasSiegeLocationIn, Fourth Crusade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasSiegeLocationIn Context triple: [Zara, wasSiegeLocationIn, Fourth Crusade]
-
A.
siegeOccurredIn
chosen
Indicates that a siege took place within or at the location specified by the related entity.
-
B.
isSiegeOf
Indicates a relationship where one event or action constitutes the military siege of a particular place, target, or entity.
-
C.
siegeRelated
Indicates a relationship in which one entity is involved with, associated with, or relevant to a siege or siege-related activities.
-
D.
wasBesiegedBy
Indicates that an entity (typically a place or stronghold) was subjected to a military siege carried out by another entity.
-
E.
besiegedIn
Indicates that one entity is under siege at, or during the event of, another specified location or time.
- 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_69f76db0fb30819096709d43f9a1f45f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.