Triple
T3166203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon Santa Apolónia railway station |
E66216
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
SAP
SAP is the station code for Lisbon Santa Apolónia, one of the main railway terminals in Lisbon, Portugal.
|
E333985
|
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: SAP | Statement: [Lisbon Santa Apolónia railway station, hasStationCode, SAP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SAP Context triple: [Lisbon Santa Apolónia railway station, hasStationCode, SAP]
-
A.
SAP
SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
-
B.
SAP
SAP was the former official currency of South Africa, used before the adoption of the South African rand.
-
C.
SAP
SAP is the commonly used abbreviation for the Société d’Anthropologie de Paris, a French learned society dedicated to the study of anthropology.
-
D.
Sap
Sap is an acoustic EP by the American rock band Alice in Chains, known for its darker, introspective sound and guest vocal appearances.
-
E.
ERP
ERP was a Salvadoran leftist guerrilla organization that became one of the key factions within the Farabundo Martí National Liberation Front (FMLN) during El Salvador’s civil war.
- 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: SAP Triple: [Lisbon Santa Apolónia railway station, hasStationCode, SAP]
Generated description
SAP is the station code for Lisbon Santa Apolónia, one of the main railway terminals in Lisbon, Portugal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SAP Target entity description: SAP is the station code for Lisbon Santa Apolónia, one of the main railway terminals in Lisbon, Portugal.
-
A.
SAP
SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
-
B.
SAP
SAP was the former official currency of South Africa, used before the adoption of the South African rand.
-
C.
SAP
SAP is the commonly used abbreviation for the Société d’Anthropologie de Paris, a French learned society dedicated to the study of anthropology.
-
D.
Sap
Sap is an acoustic EP by the American rock band Alice in Chains, known for its darker, introspective sound and guest vocal appearances.
-
E.
ERP
ERP was a Salvadoran leftist guerrilla organization that became one of the key factions within the Farabundo Martí National Liberation Front (FMLN) during El Salvador’s civil war.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada643e3e481908f4526d66e36e150 |
completed | March 8, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235e108cc81909d5733bd00cb0bee |
completed | March 12, 2026, 3:41 a.m. |
| NEDg | Description generation | batch_69b2372a54a481908a4a954b8986aad7 |
completed | March 12, 2026, 3:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b23806a3c8819096069982b3612730 |
completed | March 12, 2026, 3:50 a.m. |
Created at: March 8, 2026, 3:06 p.m.