Triple
T11146086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | INSAT-1B |
E263672
|
entity |
| Predicate | numberOfTransponders |
P98042
|
FINISHED |
| Object | 12 C-band transponders |
—
|
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: 12 C-band transponders | Statement: [INSAT-1B, numberOfTransponders, 12 C-band transponders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTransponders Context triple: [INSAT-1B, numberOfTransponders, 12 C-band transponders]
-
A.
numberOfAntennas
Indicates the quantity of antennas that an entity possesses or is associated with.
-
B.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
-
C.
numberOfSatellites
Indicates the quantity of satellites that are associated with or orbit a given entity.
-
D.
numberOfAntennasInitial
Indicates the initial count of antennas associated with an entity before any changes or updates occur.
-
E.
numberOfReceivers
Indicates the quantity of distinct receivers associated with or involved in a given entity, event, or transaction.
- F. None of above. chosen
Provenance (4 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e86e9ef48190b4df4b14319a954f |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:28 p.m.