Triple
T37261426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messapic language |
E924266
|
entity |
| Predicate | hasWordOrderEvidence |
P14924
|
FINISHED |
| Object | limited |
—
|
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: limited | Statement: [Messapic language, hasWordOrderEvidence, limited]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWordOrderEvidence Context triple: [Messapic language, hasWordOrderEvidence, limited]
-
A.
hasBasicWordOrder
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
-
B.
hasWordOrderFlexibility
Indicates that the sequence of words in a phrase or sentence can vary without changing its core grammatical correctness or meaning.
-
C.
alsoExhibitsWordOrder
Indicates that one linguistic element displays the same or an additional word order pattern as another element or construction.
-
D.
hasV2WordOrder
Indicates that a clause or language follows verb-second (V2) word order, where the finite verb consistently appears in the second position of the sentence.
-
E.
hasLanguageEvidenceOf
chosen
Indicates that there is linguistic or textual evidence supporting, documenting, or attesting to the related entity or claim.
- 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_69f76eabd6c481909d414a80a1345c98 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
Created at: May 3, 2026, 4:15 p.m.