Triple
T32924842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahá |
E842237
|
entity |
| Predicate | hasPlaceInYear |
P29100
|
FINISHED |
| Object | first month of the Bahá’í year |
—
|
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: first month of the Bahá’í year | Statement: [Bahá, hasPlaceInYear, first month of the Bahá’í year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlaceInYear Context triple: [Bahá, hasPlaceInYear, first month of the Bahá’í year]
-
A.
hasPartInYear
Indicates that something includes or contains a specific part, component, or segment that is associated with a particular year.
-
B.
hasPlaceIn
Indicates that one entity occupies, is located within, or holds a specific position in another entity or context.
-
C.
tookPlaceInYear
chosen
Indicates that an event or occurrence happened during a specific calendar year.
-
D.
hasHistoricEventYear
Indicates the specific year in which a referenced historic event took place.
-
E.
foundInYear
Indicates the specific calendar year in which something was discovered, created, established, or otherwise found.
- 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 1, 2026, 1:20 a.m.