Triple
T1350732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Count calendar |
E28874
|
entity |
| Predicate | hasStartingPoint |
P10897
|
FINISHED |
| Object | mythological creation date |
—
|
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: mythological creation date | Statement: [Long Count calendar, hasStartingPoint, mythological creation date]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStartingPoint Context triple: [Long Count calendar, hasStartingPoint, mythological creation date]
-
A.
startPoint
Indicates the initial location or position from which an object, path, or action begins.
-
B.
hasTimeStart
chosen
Indicates that an event, process, or state begins at a specific point in time.
-
C.
hasInitialPointMonument
Indicates that a monument serves as the designated initial or starting point for a referenced spatial feature or boundary.
-
D.
startsAt
Indicates that an event, process, or state begins at a specific time, location, or point in a sequence.
-
E.
beganWith
Indicates that one event, process, or state started with or was initiated by another specified event, process, or state.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c26981d081909ca3b8d8cdf7cf2e |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef5857c81909ae984feb85a26ca |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.