Triple
T25454515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mollywood |
E637876
|
entity |
| Predicate | usesScriptWritingLanguage |
P164789
|
FINISHED |
| Object | Malayalam |
—
|
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: Malayalam | Statement: [Mollywood, usesScriptWritingLanguage, Malayalam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesScriptWritingLanguage Context triple: [Mollywood, usesScriptWritingLanguage, Malayalam]
-
A.
writesLanguage
Indicates that an entity produces written content in a particular language.
-
B.
usesScriptingLanguage
Indicates that an entity employs a scripting language to perform its operations, configuration, or automation tasks.
-
C.
currentlyWrittenIn
Indicates that a work or document is, at the present time, expressed or composed in a particular language or writing system.
-
D.
usesWriting
Indicates that one entity employs or applies a particular writing system, script, or written form for communication or representation.
-
E.
screenplayLanguage
Indicates the language in which a screenplay is written or primarily expressed.
- 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_69e75db7c5048190b8da9cd7eeedb610 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f650fc44e48190bc0e0a935eac62a6 |
completed | May 2, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f650c466b881908954e43bfebae8a4 |
completed | May 2, 2026, 7:30 p.m. |
Created at: April 21, 2026, 2:04 p.m.