Triple
T26951162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S/Z |
E678779
|
entity |
| Predicate | dividesTextInto |
P147592
|
FINISHED |
| Object | 561 lexias |
—
|
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: 561 lexias | Statement: [S/Z, dividesTextInto, 561 lexias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dividesTextInto Context triple: [S/Z, dividesTextInto, 561 lexias]
-
A.
textualDivisionOf
chosen
Indicates that one text segment functions as a structural subdivision (such as a chapter, section, or paragraph) within another text.
-
B.
separatedInto
Indicates that something has been divided or split into distinct parts, groups, or components.
-
C.
isDividedFrom
Indicates that one entity is separated or partitioned from another, typically by a boundary, barrier, or dividing line.
-
D.
dividedBetween
Indicates that something is partitioned or shared among two or more distinct entities or groups.
-
E.
sometimesDividedInto
Indicates that an entity is on some occasions partitioned or separated into distinct parts, sections, or groups, but not always.
- 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_69eeeb4e75f08190b14fc91ca4a91488 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62089ffe48190b0f7ea25369b1fbf |
completed | May 2, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 6:24 a.m.