Triple
T7365358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indus script |
E169855
|
entity |
| Predicate | longestInscriptionLength |
P23293
|
FINISHED |
| Object | about 26 signs |
—
|
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: about 26 signs | Statement: [Indus script, longestInscriptionLength, about 26 signs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longestInscriptionLength Context triple: [Indus script, longestInscriptionLength, about 26 signs]
-
A.
numberOfInscriptions
Indicates the total count of inscriptions associated with a given entity or object.
-
B.
longestDurationAt
Indicates that one entity has the greatest length of time associated with a particular state, event, or activity compared to other relevant entities.
-
C.
hasNumberOfNamesInscribed
Indicates the quantity of distinct names that are inscribed on a given entity.
-
D.
hasInscriptions
Indicates that an object, surface, or artifact bears written, carved, or engraved inscriptions on it.
-
E.
maximumRecordedLength
chosen
Indicates the greatest length value that has been observed and recorded for the entity in question.
- 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_69c68a5ade988190885b7175f63b7534 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f02d36108190bcb34a95e6a30bd7 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:06 p.m.