Triple
T1977566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman Reading |
E42949
|
entity |
| Predicate | formTreatment |
P33017
|
FINISHED |
| Object | flattened |
—
|
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: flattened | Statement: [Woman Reading, formTreatment, flattened]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formTreatment Context triple: [Woman Reading, formTreatment, flattened]
-
A.
formsFrom
Indicates that one entity is created, derived, or takes shape as a result of another entity.
-
B.
typicalForm
Indicates that one entity represents the standard, characteristic, or most common form or shape in which another entity typically appears or is realized.
-
C.
formsWith
Indicates that one entity combines or associates with another to create or constitute a joint structure, group, or configuration.
-
D.
helpedForm
Indicates that one entity contributed significantly to the creation, establishment, or founding of another entity.
-
E.
filingForm
Indicates that an entity submits or completes a specific form or document, typically as part of an official or administrative process.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb42ecde881909bc9132885d8d0bd |
completed | March 7, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb09b27e88190bff164040fef6d7e |
completed | March 7, 2026, 4:59 a.m. |
Created at: March 4, 2026, 7:36 p.m.