Triple
T2526843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pi Tau Sigma |
E56053
|
entity |
| Predicate | usesGreekLetters |
P7160
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Pi Tau Sigma, usesGreekLetters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesGreekLetters Context triple: [Pi Tau Sigma, usesGreekLetters, true]
-
A.
hasNameInGreek
Indicates that an entity is associated with a specific representation of its name in the Greek language.
-
B.
hasTitleInGreek
Indicates that an entity possesses a specific title expressed in the Greek language.
-
C.
usesAlphabet
chosen
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
D.
numericValueInGreekNumerals
Indicates that a given numeric value is represented or expressed using Greek numeral notation.
-
E.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd255f0d081908d20cfb812c4bfc1 |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.