Triple
T25088028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiuhpohualli |
E628376
|
entity |
| Predicate | meaningInNahuatl |
P157628
|
FINISHED |
| Object | year count |
—
|
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: year count | Statement: [Xiuhpohualli, meaningInNahuatl, year count]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningInNahuatl Context triple: [Xiuhpohualli, meaningInNahuatl, year count]
-
A.
meaningInQuechua
Indicates that one entity expresses the meaning or translation of another entity in the Quechua language.
-
B.
textMeaning
Indicates that one text expresses, conveys, or corresponds to a particular meaning or semantic content.
-
C.
equivalentEpithetInNahuatl
Indicates that one entity’s epithet has an equivalent or corresponding epithet expressed in the Nahuatl language.
-
D.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
E.
ermenMeaning
Indicates that one entity represents or conveys the meaning or semantic interpretation of another entity.
- 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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f461e667a48190ad63646978cadf62 |
completed | May 1, 2026, 8:18 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
| PDg | Predicate description generation | batch_69f448fe11f08190bdd53ca7ba2d51e4 |
completed | May 1, 2026, 6:32 a.m. |
Created at: April 18, 2026, 6:24 a.m.