Triple
T27198148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jalaluddin Fateh Shah |
E683659
|
entity |
| Predicate | coinInscriptionLanguage |
P16790
|
FINISHED |
| Object | Persian |
—
|
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: Persian | Statement: [Jalaluddin Fateh Shah, coinInscriptionLanguage, Persian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coinInscriptionLanguage Context triple: [Jalaluddin Fateh Shah, coinInscriptionLanguage, Persian]
-
A.
inscriptionsLanguage
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
B.
bellInscriptionLanguage
Indicates the language in which the inscription on a bell is written.
-
C.
languageOnCoins
chosen
Indicates the language that is inscribed or used on a set of coins.
-
D.
issuedInscription
Indicates that an authority or source formally created and released a specific inscription or written record.
-
E.
issuedInscriptionsIn
Indicates that an entity (such as an authority or issuer) produced or authorized inscriptions within a specified place or context.
- 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_69eefad1fd5c8190a4a46ea6afe58bfa |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f625b229f08190ae2517727533105d |
completed | May 2, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 9:35 a.m.