Triple
T6608107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dock10 |
E149168
|
entity |
| Predicate | hasStudio |
P30541
|
FINISHED |
| Object |
HQ7
HQ7 is one of the television production studios within Dock10’s media facility at MediaCityUK in Salford, England.
|
E606843
|
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: HQ7 | Statement: [Dock10, hasStudio, HQ7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HQ7 Context triple: [Dock10, hasStudio, HQ7]
-
A.
QH
QH is the standard abbreviation for Qinghai, a large inland province in northwestern China known for the Qinghai-Tibet Plateau and Qinghai Lake.
-
B.
J7
J7 is a numbered junction on the M60 motorway in Greater Manchester, England, serving as an access point between the motorway and the surrounding local road network.
-
C.
KQ
KQ is the IATA airline designator for Kenya Airways, the flag carrier of Kenya.
-
D.
K7
K7 is the registration number of the Bluebird K7, the famous mid-20th-century hydroplane in which Donald Campbell set multiple world water speed records.
-
E.
HM7B
The HM7B is a European cryogenic rocket engine that powers the upper stages of Ariane launch vehicles, providing precise orbital insertion using liquid hydrogen and liquid oxygen propellants.
- 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: HQ7 Triple: [Dock10, hasStudio, HQ7]
Generated description
HQ7 is one of the television production studios within Dock10’s media facility at MediaCityUK in Salford, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HQ7 Target entity description: HQ7 is one of the television production studios within Dock10’s media facility at MediaCityUK in Salford, England.
-
A.
QH
QH is the standard abbreviation for Qinghai, a large inland province in northwestern China known for the Qinghai-Tibet Plateau and Qinghai Lake.
-
B.
J7
J7 is a numbered junction on the M60 motorway in Greater Manchester, England, serving as an access point between the motorway and the surrounding local road network.
-
C.
KQ
KQ is the IATA airline designator for Kenya Airways, the flag carrier of Kenya.
-
D.
K7
K7 is the registration number of the Bluebird K7, the famous mid-20th-century hydroplane in which Donald Campbell set multiple world water speed records.
-
E.
HM7B
The HM7B is a European cryogenic rocket engine that powers the upper stages of Ariane launch vehicles, providing precise orbital insertion using liquid hydrogen and liquid oxygen propellants.
- 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_69c687eaa7508190bb58ce2aa02039b3 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af31c4748190ab5027771c9ce5b2 |
completed | March 27, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e43cc42081909762eec710773f40 |
completed | March 27, 2026, 8:10 p.m. |
| NEDg | Description generation | batch_69c6e57d71ec8190b79615f11eadec26 |
completed | March 27, 2026, 8:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6e614f04c8190b25b553553895799 |
completed | March 27, 2026, 8:18 p.m. |
Created at: March 27, 2026, 1:57 p.m.