Triple
T1728528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oto-Manguean languages |
E37554
|
entity |
| Predicate | hasHistoricalDepth |
P1409
|
FINISHED |
| Object | ancient |
—
|
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: ancient | Statement: [Oto-Manguean languages, hasHistoricalDepth, ancient]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalDepth Context triple: [Oto-Manguean languages, hasHistoricalDepth, ancient]
-
A.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
-
B.
hasInflationHistory
Indicates that an entity is associated with a recorded or known pattern of inflation over time.
-
C.
hasHistoricalShiftTo
Indicates a change over time in which one state, condition, or configuration is replaced or transformed into another in a historically traceable way.
-
D.
hasHistoricalContext
chosen
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
-
E.
hasHistoricQuarter
Indicates that an entity possesses or contains a historically significant district or quarter as part of its area or structure.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aadb7bda1081908f2c41c520c9c55c |
completed | March 6, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61c0a0288190bce9d60062a84b69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.