Triple
T300391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HL7 standards |
E6183
|
entity |
| Predicate | firstVersionReleaseYear |
P3297
|
FINISHED |
| Object | 1987 |
—
|
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: 1987 | Statement: [HL7 standards, firstVersionReleaseYear, 1987]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstVersionReleaseYear Context triple: [HL7 standards, firstVersionReleaseYear, 1987]
-
A.
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.
-
B.
firstDeployed
Indicates the time or event when something (such as a system, product, or resource) was initially put into active use or operation.
-
C.
introducedInYear
chosen
Indicates the year in which something was first introduced, launched, or made available.
-
D.
wasFirstBuiltInYear
Indicates that the initial construction of an entity was completed in a specified year.
-
E.
firstSuccessfulLaunchDate
Indicates the calendar date on which an entity achieved its first successful launch.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.