Triple
T38079213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zēngzhǎng Tiānwáng |
E950804
|
entity |
| Predicate | counterpartNameInSanskrit |
P207584
|
FINISHED |
| Object | Virūḍhaka |
E282155
|
NE 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: Virūḍhaka | Statement: [Zēngzhǎng Tiānwáng, counterpartNameInSanskrit, Virūḍhaka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: counterpartNameInSanskrit Context triple: [Zēngzhǎng Tiānwáng, counterpartNameInSanskrit, Virūḍhaka]
-
A.
counterpartEnglishName
Indicates that an entity has a corresponding counterpart whose name is given in English.
-
B.
hasCounterpartName
Indicates that an entity has an alternative or corresponding name used as its counterpart in another context, system, or representation.
-
C.
hasCounterpartNameLanguage
Indicates that an entity’s counterpart (e.g., in another context or system) has a name expressed in a specified language.
-
D.
counterpartTerm
Indicates that one term serves as a corresponding or equivalent term to another within a specific relational or comparative context.
-
E.
hasCounterpartNickname
Indicates that one entity is used as an alternative or counterpart nickname for another entity.
- F. None of above. chosen
Provenance (5 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4193b3907881908ff7ba8e3596aff4 |
completed | June 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037df009f4819082e04683e6e8a106 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:21 p.m.