Triple
T21073061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi–Meerut Expressway |
E519156
|
entity |
| Predicate | openingYearOfFirstSection |
P20181
|
FINISHED |
| Object | 2018 |
—
|
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: 2018 | Statement: [Delhi–Meerut Expressway, openingYearOfFirstSection, 2018]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingYearOfFirstSection Context triple: [Delhi–Meerut Expressway, openingYearOfFirstSection, 2018]
-
A.
openingDateOfFirstSpan
Indicates the date on which the first span (e.g., of a structure or project) was initially opened or put into service.
-
B.
firstSectionOpened
chosen
Indicates that the initial section in a sequence or structure has been opened or activated.
-
C.
firstSectionOpenedBetween
Indicates that the first section was opened at some point within a specified time interval or between two defined events.
-
D.
firstSeriesYear
Indicates the year in which a series (such as a TV show, book series, or sports league season) first began or was initially released.
-
E.
inscriptionYearOfFirstElements
Indicates the year in which the first elements of something (such as a site, object, or collection) were officially inscribed or recorded in a designated register or list.
- 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_69e0b506e59c8190849b71ed07929215 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e702d491a08190a9f5f28c0b72d38c |
completed | April 21, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:47 p.m.