Triple
T16576876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pithoigia |
E402734
|
entity |
| Predicate | timeWithinYear |
P31250
|
FINISHED |
| Object | month of Anthesterion |
—
|
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: month of Anthesterion | Statement: [Pithoigia, timeWithinYear, month of Anthesterion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeWithinYear Context triple: [Pithoigia, timeWithinYear, month of Anthesterion]
-
A.
approximateTimeInYear
Indicates that one time-related entity represents an estimated or non-exact point or interval within a given year for another entity.
-
B.
timePeriodWithin
Indicates that one time period is entirely contained within the bounds of another time period.
-
C.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
D.
yearPassed
Indicates that a specified number of calendar years has elapsed between two time points or events.
-
E.
timeOfYearPlayed
chosen
Indicates the specific time or season of the year during which an event or activity is performed or takes place.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3595dd90881909933216bd12505e1 |
completed | April 18, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69e296a7d9d0819088555bca6c936e79 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.