Triple
T5075559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hastinapura |
E114385
|
entity |
| Predicate | traditionalEtymology |
P61271
|
FINISHED |
| Object | city of the elephant |
—
|
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: city of the elephant | Statement: [Hastinapura, traditionalEtymology, city of the elephant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalEtymology Context triple: [Hastinapura, traditionalEtymology, city of the elephant]
-
A.
etymology
Indicates the historical origin and development of a word or term, including its source language and form.
-
B.
etymologicalField
Indicates that one term belongs to a particular semantic or conceptual domain relevant to its etymological origin or historical development.
-
C.
popularEtymology
Indicates that an etymological explanation is based on common belief or folk interpretation rather than on historically or linguistically accurate origins.
-
D.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
E.
etymologicalLanguage
Indicates the language from which a word or term is historically derived in its etymology.
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74d2243481908c1ae62f7123c4e9 |
completed | March 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69bd7157fe608190b4515d56fdd0a616 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd73d90b608190bd6c2407e84e2b64 |
completed | March 20, 2026, 4:20 p.m. |
Created at: March 20, 2026, 1:39 p.m.