Triple
T15410000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tramway T11 Express |
E368560
|
entity |
| Predicate | lineNumber |
P1864
|
FINISHED |
| Object |
T11
T11 is a tram-train line of the Île-de-France public transport network serving the northern suburbs of Paris.
|
E1154201
|
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: T11 | Statement: [Tramway T11 Express, lineNumber, T11]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T11 Context triple: [Tramway T11 Express, lineNumber, T11]
-
A.
T11
T11 is the FAA location identifier assigned to Yap International Airport in the Federated States of Micronesia.
-
B.
T10
T10 is a technical committee under INCITS responsible for developing standards for SCSI (Small Computer System Interface) and related storage interfaces.
-
C.
T1
T1 is one of the tram routes of the Trambaix light rail network serving the Barcelona metropolitan area.
-
D.
T1
T1 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit across key parts of the city.
-
E.
T1
T1 is a tram line serving the Lyon metropolitan area in France, connecting key districts including Villeurbanne.
- 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: T11 Triple: [Tramway T11 Express, lineNumber, T11]
Generated description
T11 is a tram-train line of the Île-de-France public transport network serving the northern suburbs of Paris.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T11 Target entity description: T11 is a tram-train line of the Île-de-France public transport network serving the northern suburbs of Paris.
-
A.
T11
T11 is the FAA location identifier assigned to Yap International Airport in the Federated States of Micronesia.
-
B.
T10
T10 is a technical committee under INCITS responsible for developing standards for SCSI (Small Computer System Interface) and related storage interfaces.
-
C.
T1
T1 is one of the tram routes of the Trambaix light rail network serving the Barcelona metropolitan area.
-
D.
T1
T1 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit across key parts of the city.
-
E.
T1
T1 is a tram line serving the Lyon metropolitan area in France, connecting key districts including Villeurbanne.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea4f13c819085d26fd32b5dca6f |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff135d65988190b35392bdf1e45985 |
completed | May 9, 2026, 10:58 a.m. |
| NEDg | Description generation | batch_69ff14042ce8819084817836b096f175 |
completed | May 9, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff14745a8c81909b10d6b21b88b50b |
completed | May 9, 2026, 11:03 a.m. |
Created at: April 10, 2026, 3:20 a.m.