Triple
T35707485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FINAL PE |
E1031756
|
entity |
| Predicate | orthographicFunction |
P11939
|
FINISHED |
| Object | marks word-final position of Pe |
—
|
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: marks word-final position of Pe | Statement: [FINAL PE, orthographicFunction, marks word-final position of Pe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orthographicFunction Context triple: [FINAL PE, orthographicFunction, marks word-final position of Pe]
-
A.
orthographicProperty
Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
-
B.
orthographicChange
Indicates a relationship where one written form of a word or expression has been altered into another through changes in spelling or orthography.
-
C.
orthographicGoal
Indicates that one entity has the intended or target written/orthographic form of another entity.
-
D.
orthographicLength
Indicates the number of written characters or symbols used to represent an entity in a particular orthographic form.
-
E.
orthographicRole
chosen
Indicates the functional role that a written form or spelling plays within an orthographic system (e.g., as a letter, diacritic, punctuation mark, or other script element).
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.