Triple
T374144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Council of Constantinople |
E8332
|
entity |
| Predicate | numberOfCanons |
P13053
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [First Council of Constantinople, numberOfCanons, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCanons Context triple: [First Council of Constantinople, numberOfCanons, 4]
-
A.
usesCanons
Indicates that one entity employs or makes use of canons (such as rules, principles, or artillery pieces) in relation to another entity or context.
-
B.
numberOfTanks
Indicates the quantity or count of tanks associated with a given entity or context.
-
C.
numberOfTowers
Indicates the quantity of towers associated with or contained by a given entity.
-
D.
numberOfTargets
Indicates the quantity of target entities associated with or affected by a given subject or event.
-
E.
numberOfInvaders
Indicates the quantity of entities classified as invaders associated with a given subject or context.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec13b9b48190b294d998c6720132 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96216048190873ae533fa5b864d |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ebcb1b2c8190a68bb3bad600c227 |
completed | Feb. 28, 2026, 1:21 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.