Triple
T2141219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob of Serugh |
E46762
|
entity |
| Predicate | approximateNumberOfHomilies |
P37067
|
FINISHED |
| Object | over 700 attributed |
—
|
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: over 700 attributed | Statement: [Jacob of Serugh, approximateNumberOfHomilies, over 700 attributed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfHomilies Context triple: [Jacob of Serugh, approximateNumberOfHomilies, over 700 attributed]
-
A.
approximateNumberOfVerses
Indicates an estimated or approximate count of verses associated with an entity.
-
B.
approximateNumberOfTractates
Indicates a relationship where an entity is associated with an estimated or non-exact count of tractates linked to it.
-
C.
approximateNumberOfPoems
Indicates an estimated or roughly calculated count of poems associated with an entity.
-
D.
numberOfMonksApprox
Indicates an approximate count or estimate of how many monks are involved or present in a given context.
-
E.
hasApproximateTotalSpeakers
Indicates that an entity is associated with an estimated or roughly calculated number of total speakers, rather than an exact count.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbf74147c81908793c3694894f94a |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbd96a3b0819081efbfef975e1513 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf71edf08190add69022aabfd49d |
completed | March 7, 2026, 6:02 a.m. |
Created at: March 4, 2026, 7:44 p.m.