Triple
T17131430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESA ESTRACK network |
E415728
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Kourou Station
Kourou Station is a European Space Agency ground tracking facility in French Guiana that supports communication and control for spacecraft as part of the ESTRACK network.
|
E1263431
|
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: Kourou Station | Statement: [ESA ESTRACK network, hasPart, Kourou Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kourou Station Context triple: [ESA ESTRACK network, hasPart, Kourou Station]
-
A.
Kiwa Station
Kiwa Station is a railway station in Wakayama Prefecture, Japan, serving passengers on the Wakayamakō Line.
-
B.
Ageo Station
Ageo Station is a railway station in Ageo, Saitama Prefecture, Japan, serving as a stop on the JR East Takasaki Line.
-
C.
Roa Station
Roa Station is a railway station serving the municipality of Lunner in Viken county, Norway.
-
D.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
-
E.
Naha Station
Naha Station is a major railway terminal in Naha, Okinawa, serving as a key transportation hub for the city and surrounding region.
- 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: Kourou Station Triple: [ESA ESTRACK network, hasPart, Kourou Station]
Generated description
Kourou Station is a European Space Agency ground tracking facility in French Guiana that supports communication and control for spacecraft as part of the ESTRACK network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kourou Station Target entity description: Kourou Station is a European Space Agency ground tracking facility in French Guiana that supports communication and control for spacecraft as part of the ESTRACK network.
-
A.
Kiwa Station
Kiwa Station is a railway station in Wakayama Prefecture, Japan, serving passengers on the Wakayamakō Line.
-
B.
Ageo Station
Ageo Station is a railway station in Ageo, Saitama Prefecture, Japan, serving as a stop on the JR East Takasaki Line.
-
C.
Roa Station
Roa Station is a railway station serving the municipality of Lunner in Viken county, Norway.
-
D.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
-
E.
Naha Station
Naha Station is a major railway terminal in Naha, Okinawa, serving as a key transportation hub for the city and surrounding region.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f02a9fbc81909d820d29417aa55c |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c36b32c8190a365b7b80207978c |
completed | May 11, 2026, 7:58 a.m. |
| NEDg | Description generation | batch_6a018d86c7808190b9de682e49d4295c |
completed | May 11, 2026, 8:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a018e57fa708190872ad2fb5f660507 |
completed | May 11, 2026, 8:07 a.m. |
Created at: April 10, 2026, 5:36 a.m.