Triple
T5535737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid Chamartín railway station |
E145156
|
entity |
| Predicate | railwayStationCode |
P1289
|
FINISHED |
| Object |
ESMCH
ESMCH is the station code used to identify Madrid Chamartín, one of the main railway stations in Madrid, Spain.
|
E531904
|
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: ESMCH | Statement: [Madrid Chamartín railway station, railwayStationCode, ESMCH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ESMCH Context triple: [Madrid Chamartín railway station, railwayStationCode, ESMCH]
-
A.
ESM
ESM is an intergovernmental financial institution of the eurozone that provides financial assistance to member states in economic distress to safeguard financial stability.
-
B.
ESM
ESM is the abbreviation for NASA’s Exceptional Service Medal, an honor awarded to individuals for significant, sustained contributions to the agency’s mission.
-
C.
EMES
EMES is the abbreviated name for the Europe and Middle East Section, an organizational division focused on activities and interests spanning those two regions.
-
D.
ES-MD
ES-MD is the ISO 3166-2 subdivision code that uniquely identifies Spain’s Community of Madrid.
-
E.
ESH
ESH is the IATA airport code for Shoreham-by-Sea airfield, a regional airport on the south coast of England.
- 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: ESMCH Triple: [Madrid Chamartín railway station, railwayStationCode, ESMCH]
Generated description
ESMCH is the station code used to identify Madrid Chamartín, one of the main railway stations in Madrid, Spain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ESMCH Target entity description: ESMCH is the station code used to identify Madrid Chamartín, one of the main railway stations in Madrid, Spain.
-
A.
ESM
ESM is the abbreviation for NASA’s Exceptional Service Medal, an honor awarded to individuals for significant, sustained contributions to the agency’s mission.
-
B.
ESM
ESM is an intergovernmental financial institution of the eurozone that provides financial assistance to member states in economic distress to safeguard financial stability.
-
C.
EMES
EMES is the abbreviated name for the Europe and Middle East Section, an organizational division focused on activities and interests spanning those two regions.
-
D.
ES-MD
ES-MD is the ISO 3166-2 subdivision code that uniquely identifies Spain’s Community of Madrid.
-
E.
ESH
ESH is the IATA airport code for Shoreham-by-Sea airfield, a regional airport on the south coast of England.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01faed1d08190b6a57faedaf1b56a |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02814359c8190b868811f22aa568c |
completed | March 22, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69c04441145481909fb7bd26dab129bd |
completed | March 22, 2026, 7:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c044a919ec81909469793af9f837ea |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:34 p.m.