Triple
T12676161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of Goa |
E302816
|
entity |
| Predicate | assemblyTermLength |
P48410
|
FINISHED |
| Object | 5 years |
—
|
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: 5 years | Statement: [Government of Goa, assemblyTermLength, 5 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assemblyTermLength Context triple: [Government of Goa, assemblyTermLength, 5 years]
-
A.
assemblyTerm
Indicates that an entity is associated with, or occurs during, a specific legislative or organizational assembly term.
-
B.
headTermLength
Indicates that a term (such as a word or phrase) has a specified length, typically measured in characters or tokens.
-
C.
positionTermLength
chosen
Indicates the duration or length of time associated with holding a particular position or role.
-
D.
hasNumberOfTerms
Indicates the quantity of distinct terms or elements associated with a given entity or expression.
-
E.
lengthInWords
Indicates the number of words that make up the length of something, typically a text or expression.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b0d9c88190a05d6cbcb7a1642d |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.