Triple
T11387752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Institut d’Optique Graduate School |
E269752
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
SupOptique
SupOptique is a leading French grande école specializing in optics, photonics, and related engineering and research.
|
E923407
|
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: SupOptique | Statement: [Institut d’Optique Graduate School, alsoKnownAs, SupOptique]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SupOptique Context triple: [Institut d’Optique Graduate School, alsoKnownAs, SupOptique]
-
A.
Opal Telecom
Opal Telecom was a UK-based telecommunications provider that became part of TalkTalk’s business services operations following its acquisition.
-
B.
Cogent Communications
Cogent Communications is a multinational internet service provider specializing in high-speed fiber-optic connectivity and IP transit services for businesses and carriers.
-
C.
Optica
Optica is a leading scientific society dedicated to advancing the study and application of optics and photonics worldwide.
-
D.
OXC
OXC is the three-letter station code for Oxford Circus, a major London Underground interchange in the West End.
-
E.
Opti
Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
- 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: SupOptique Triple: [Institut d’Optique Graduate School, alsoKnownAs, SupOptique]
Generated description
SupOptique is a leading French grande école specializing in optics, photonics, and related engineering and research.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SupOptique Target entity description: SupOptique is a leading French grande école specializing in optics, photonics, and related engineering and research.
-
A.
Opal Telecom
Opal Telecom was a UK-based telecommunications provider that became part of TalkTalk’s business services operations following its acquisition.
-
B.
Cogent Communications
Cogent Communications is a multinational internet service provider specializing in high-speed fiber-optic connectivity and IP transit services for businesses and carriers.
-
C.
Optica
Optica is a leading scientific society dedicated to advancing the study and application of optics and photonics worldwide.
-
D.
OXC
OXC is the three-letter station code for Oxford Circus, a major London Underground interchange in the West End.
-
E.
Opti
Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7fc389d4c81909515a5c8b0099c36 |
completed | April 9, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58c672da48190affacc0f19ef0c7a |
completed | April 20, 2026, 2:16 a.m. |
| NEDg | Description generation | batch_69e59774e6648190a38b2515a83c2e0c |
completed | April 20, 2026, 3:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5a3abf24481908fb71f4ef6b13532 |
completed | April 20, 2026, 3:55 a.m. |
Created at: April 8, 2026, 9:34 p.m.