Triple
T3909130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruqʿah |
E87278
|
entity |
| Predicate | letterShapeFeature |
P1464
|
FINISHED |
| Object | rounded forms for many letters |
—
|
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: rounded forms for many letters | Statement: [Ruqʿah, letterShapeFeature, rounded forms for many letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: letterShapeFeature Context triple: [Ruqʿah, letterShapeFeature, rounded forms for many letters]
-
A.
hasDistinctLetterForms
Indicates that the related writing system or symbol set uses different visual shapes or styles for the same letter in different contexts (such as position, case, or usage).
-
B.
shape
chosen
Indicates that one entity has a particular geometric or physical form characterized by the other entity.
-
C.
leafShape
Indicates the characteristic form or outline of a leaf that an entity possesses or exhibits.
-
D.
heightPerLetter
Indicates the vertical size or height assigned to each individual letter in a text or font.
-
E.
textCharacter
Indicates that one entity is a character (such as a letter, digit, or symbol) within a piece of text associated with another entity.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.