Triple
T17102680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SLIM |
E415017
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | SLIM |
E415017
|
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: SLIM | Statement: [SLIM, acronym, SLIM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SLIM Context triple: [SLIM, acronym, SLIM]
-
A.
SLIM
chosen
SLIM is a Japanese lunar lander mission developed by JAXA to demonstrate high-precision, lightweight Moon-landing technology.
-
B.
Slim
Slim is the surname of Carlos Slim Helú, the Mexican business magnate and one of the world's richest individuals.
-
C.
Slim
Slim is a lightweight Ruby templating engine known for its minimal syntax and fast rendering performance.
-
D.
Slim
Slim is the nickname of Slim Keith, a prominent American socialite and fashion icon of the mid-20th century known for her influence in high society and style.
-
E.
Slim
Slim is a given name or nickname commonly used for people with a slender build or as a casual moniker in various English-speaking cultures.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2495c88190b5b16a006a994faf |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139ffbe808190a24e827331ee4a6c |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.