Triple
T21111241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abhangas of Namdev |
E520174
|
entity |
| Predicate | meterForm |
P142894
|
FINISHED |
| Object | abhang |
—
|
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: abhang | Statement: [Abhangas of Namdev, meterForm, abhang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meterForm Context triple: [Abhangas of Namdev, meterForm, abhang]
-
A.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
B.
meterSystem
Indicates that one entity uses, is measured in, or is associated with a particular system of meters or measurement units.
-
C.
metricForm
Indicates that one entity is expressed or represented in a particular metric form or measurement format relative to another.
-
D.
mètre
Indicates a measurement relationship where one entity serves as the unit "meter" used to quantify the length, distance, or size of another entity.
-
E.
metre
Indicates a measurement relationship where one entity’s length, distance, or size is quantified in units of metres.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72101f7308190beb202a052ff04d2 |
completed | April 21, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:54 p.m.