Triple
T17475850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESRO-2B |
E425535
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object |
IRIS-B
IRIS-B was a European Space Research Organisation scientific satellite used primarily for studying solar and cosmic X-ray and gamma-ray emissions in Earth orbit.
|
E1270956
|
NE FINISHED |
How this triple was built (4 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: IRIS-B | Statement: [ESRO-2B, alternativeName, IRIS-B]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IRIS-B Context triple: [ESRO-2B, alternativeName, IRIS-B]
-
A.
IRS-1B
IRS-1B is an Indian remote sensing satellite in the IRS series used primarily for Earth observation and resource monitoring.
-
B.
IRS-1D
IRS-1D is an Indian remote sensing satellite in the IRS series used primarily for Earth observation and resource monitoring.
-
C.
IRS-1C
IRS-1C is an Indian remote sensing satellite in the IRS series used primarily for Earth observation and resource monitoring.
-
D.
IRIS GL
IRIS GL is an early proprietary 3D graphics application programming interface developed by Silicon Graphics that served as a precursor to OpenGL.
-
E.
ISIR
ISIR is a research institute focused on advancing scientific and industrial technologies through interdisciplinary research and innovation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: IRIS-B Triple: [ESRO-2B, alternativeName, IRIS-B]
Generated description
IRIS-B was a European Space Research Organisation scientific satellite used primarily for studying solar and cosmic X-ray and gamma-ray emissions in Earth orbit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: IRIS-B Target entity description: IRIS-B was a European Space Research Organisation scientific satellite used primarily for studying solar and cosmic X-ray and gamma-ray emissions in Earth orbit.
-
A.
IRS-1B
IRS-1B is an Indian remote sensing satellite in the IRS series used primarily for Earth observation and resource monitoring.
-
B.
IRS-1D
IRS-1D is an Indian remote sensing satellite in the IRS series used primarily for Earth observation and resource monitoring.
-
C.
IRS-1C
IRS-1C is an Indian remote sensing satellite in the IRS series used primarily for Earth observation and resource monitoring.
-
D.
IRIS GL
IRIS GL is an early proprietary 3D graphics application programming interface developed by Silicon Graphics that served as a precursor to OpenGL.
-
E.
ISIR
ISIR is a research institute focused on advancing scientific and industrial technologies through interdisciplinary research and innovation.
- F. None of above. chosen
Provenance (5 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451bb7050819080e3873bcc8a950c |
completed | April 19, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01b82d9ec081908fe296115af1729e |
completed | May 11, 2026, 11:06 a.m. |
| NEDg | Description generation | batch_6a01b97319388190a7cd0b4f667ef16b |
completed | May 11, 2026, 11:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01ba2390c08190b4077b1fe679eade |
completed | May 11, 2026, 11:14 a.m. |
Created at: April 10, 2026, 5:47 a.m.