Triple
T21573133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Space Environmental Effects Laboratory |
E532331
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | SEEL |
—
|
NE NERFINISHED |
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: SEEL | Statement: [Space Environmental Effects Laboratory, abbreviation, SEEL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SEEL Context triple: [Space Environmental Effects Laboratory, abbreviation, SEEL]
-
A.
SEEL
chosen
SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
-
B.
Sel
Sel is a municipality in Innlandet county, Norway, known for its mountainous landscapes and location in the Gudbrandsdalen valley.
-
C.
Sele
The Sele is a river in southwestern Italy that flows through the Campania region into the Tyrrhenian Sea.
-
D.
SEBL
SEBL was the stock ticker symbol for Siebel Systems, a prominent customer relationship management (CRM) software company later acquired by Oracle.
-
E.
Seille
Seille is a river in eastern France that flows through the regions of Jura and Saône-et-Loire before joining the Saône.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c4618bec8190bcb0feb74568cbb1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9ce230c81909e12bd59497e2237 |
completed | April 27, 2026, 4:45 a.m. |
Created at: April 16, 2026, 6:30 p.m.