Triple
T1082890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ACT |
E23985
|
entity |
| Predicate | hasOptionalSection |
P23744
|
FINISHED |
| Object | Writing |
—
|
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: Writing | Statement: [ACT, hasOptionalSection, Writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOptionalSection Context triple: [ACT, hasOptionalSection, Writing]
-
A.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
B.
hasChildrenSection
Indicates that an entity includes or is associated with a dedicated section that contains information about its children.
-
C.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
D.
hasLowLevelSection
Indicates that an entity includes or is associated with a subordinate or lower-level section within a larger hierarchical structure.
-
E.
hasSectionInvolved
Indicates that a particular section or subdivision is involved or participates in a specified relationship, process, or context.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95e56948190a1e92367ad7240b7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73f4310819086281f8ec67d1a32 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.