Triple
T35023154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earth–Moon Lagrange region |
E1010249
|
entity |
| Predicate | hasNumberOfLagrangePoints |
P198123
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Earth–Moon Lagrange region, hasNumberOfLagrangePoints, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfLagrangePoints Context triple: [Earth–Moon Lagrange region, hasNumberOfLagrangePoints, 5]
-
A.
LagrangePointType
Indicates the specific category or type of Lagrange point associated with a gravitational system (e.g., L1–L5).
-
B.
hasLagrangian
Indicates that a physical system or theory is associated with a specific Lagrangian function that characterizes its dynamics.
-
C.
hasNumberOfKnownMoons
Indicates the relationship that specifies how many moons are known to orbit a given celestial body.
-
D.
hasApproximateNumberOfKnownMoons
Indicates that an entity is associated with an estimated or non-exact count of moons known to orbit it.
-
E.
isLagrangianSatelliteOf
Indicates that one celestial body occupies a Lagrangian point and thus functions as a gravitationally bound satellite associated with another primary body.
- 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_69f76dccf0108190af43b465d3750196 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fecb4d02f881909a9ee97ce98000d5 |
completed | May 9, 2026, 5:51 a.m. |
| PD | Predicate disambiguation | batch_69fec9846c1c8190b317f0711f0755db |
completed | May 9, 2026, 5:43 a.m. |
| PDg | Predicate description generation | batch_69fecb4be24481908bda6197d7fc32f4 |
completed | May 9, 2026, 5:51 a.m. |
Created at: May 3, 2026, 4:01 p.m.