Triple
T2268165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malayalam script |
E50594
|
entity |
| Predicate | hasOrthographicDepth |
P12752
|
FINISHED |
| Object | relatively shallow |
—
|
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: relatively shallow | Statement: [Malayalam script, hasOrthographicDepth, relatively shallow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrthographicDepth Context triple: [Malayalam script, hasOrthographicDepth, relatively shallow]
-
A.
hasOrthographicPreference
Indicates that one entity prefers or selects a particular written or spelling form of another entity.
-
B.
orthographicProperty
chosen
Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
-
C.
hasApproximateDepth
Indicates that an entity is associated with a depth value that is not exact but estimated or approximate.
-
D.
hasOrthographicReform
Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
-
E.
hasOrientation
Indicates that one entity is positioned or directed in a specific spatial or conceptual alignment relative to a reference frame or 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.