Triple
T4093939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IAS machine |
E87767
|
entity |
| Predicate | firstOperational |
P13819
|
FINISHED |
| Object | 1951 |
—
|
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: 1951 | Statement: [IAS machine, firstOperational, 1951]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstOperational Context triple: [IAS machine, firstOperational, 1951]
-
A.
firstOperationalUse
chosen
Indicates the point in time or context when something is used operationally for the very first time.
-
B.
firstOfficialUse
Indicates the earliest point in time when something was formally or officially put into use.
-
C.
firstGeneratorCommissioned
Indicates that the first generator in a system or facility has been officially put into operation or brought online.
-
D.
firstFlight
Indicates that the associated event or record corresponds to the earliest or initial flight taken or performed by the referenced entity.
-
E.
firstOperationalCrewFlightYear
Indicates the year in which the first operational crewed flight associated with the subject took place.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefcda2f408190bcf2b64535193162 |
completed | March 9, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:40 p.m.