Triple
T15689615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Petite Reine |
E380291
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Le Mac
Le Mac is a French film associated with the production company La Petite Reine, known for its blend of crime and comedy elements.
|
E1171604
|
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: Le Mac | Statement: [La Petite Reine, notableWork, Le Mac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Mac Context triple: [La Petite Reine, notableWork, Le Mac]
-
A.
MacIntosh
MacIntosh is a Scottish-origin surname borne by various notable individuals in fields such as acting, politics, and academia.
-
B.
iMac
The iMac is Apple’s all-in-one desktop computer line known for integrating powerful hardware with a slim, minimalist display-focused design.
-
C.
Mac mini
The Mac mini is a compact desktop computer designed by Apple that offers full macOS functionality in a small, versatile form factor suitable for both consumer and professional use.
-
D.
MacBook
MacBook is Apple’s line of macOS-based laptop computers known for their sleek design, high-resolution displays, and tight hardware–software integration.
-
E.
Apple One
Apple One is Apple’s subscription bundle that combines multiple services like iCloud storage, music, video, fitness, and news into a single monthly plan.
- 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: Le Mac Triple: [La Petite Reine, notableWork, Le Mac]
Generated description
Le Mac is a French film associated with the production company La Petite Reine, known for its blend of crime and comedy elements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Le Mac Target entity description: Le Mac is a French film associated with the production company La Petite Reine, known for its blend of crime and comedy elements.
-
A.
MacIntosh
MacIntosh is a Scottish-origin surname borne by various notable individuals in fields such as acting, politics, and academia.
-
B.
iMac
The iMac is Apple’s all-in-one desktop computer line known for integrating powerful hardware with a slim, minimalist display-focused design.
-
C.
Mac mini
The Mac mini is a compact desktop computer designed by Apple that offers full macOS functionality in a small, versatile form factor suitable for both consumer and professional use.
-
D.
MacBook
MacBook is Apple’s line of macOS-based laptop computers known for their sleek design, high-resolution displays, and tight hardware–software integration.
-
E.
Apple One
Apple One is Apple’s subscription bundle that combines multiple services like iCloud storage, music, video, fitness, and news into a single monthly plan.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4e59988190aaf12f6a07c8f0e4 |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee91340819086c8f51e8eb477aa |
completed | May 9, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69ff6fd9c968819098b2552a9deb0445 |
completed | May 9, 2026, 5:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff708d42448190a53b90e00721eaa5 |
completed | May 9, 2026, 5:36 p.m. |
Created at: April 10, 2026, 4:44 a.m.