Triple
T12175018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun–Earth L2 |
E290065
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | L2 |
E290065
|
NE 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: L2 | Statement: [Sun–Earth L2, alsoKnownAs, L2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: L2 Context triple: [Sun–Earth L2, alsoKnownAs, L2]
-
A.
L2
chosen
L2 is the second Sun–Earth Lagrange point, a gravitationally stable location in space used by space telescopes such as the James Webb Space Telescope for observation.
-
B.
L2
L2 is the common shorthand for Ligue 2, the second tier of professional football in the French league system.
-
C.
L2
L2 is the commonly used designation for Line 2 of the Barcelona Metro, a rapid transit line serving several central and northern districts of the city.
-
D.
L2M
L2M is a DARPA research initiative focused on developing AI systems capable of continuous, lifelong learning and adaptation.
-
E.
L3
L3 is a particle physics experiment that operated at CERN’s Large Electron–Positron Collider, designed to study high-energy electron–positron collisions and probe the Standard Model.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915dc71788190bdaadf7be9d8d6ce |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6a9482481909500c216f23fceb4 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.