Triple
T15258005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trenitalia |
E364696
|
entity |
| Predicate | fleet |
P6198
|
FINISHED |
| Object |
ETR 610
The ETR 610 is a high-speed tilting electric multiple unit train used on international and domestic services in Italy and neighboring countries.
|
E1146933
|
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: ETR 610 | Statement: [Trenitalia, fleet, ETR 610]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ETR 610 Context triple: [Trenitalia, fleet, ETR 610]
-
A.
ETD
ETD is the ICAO airline designator used to identify Etihad Airways in international aviation operations and communications.
-
B.
E313
E313 is a major Belgian motorway connecting Antwerp with Liège and serving as a key east–west transport corridor through the Limburg region.
-
C.
ETM
ETM is the IATA airport code for Ramon Airport, an international airport serving the Eilat region in southern Israel.
-
D.
ETM
ETM is the stock ticker symbol for Audacy, Inc., a major American radio broadcasting and digital audio company formerly known as Entercom Communications.
-
E.
ETU
ETU is the commonly used abbreviation for Erzurum Technical University, a public higher education institution located in Erzurum, Turkey.
- 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: ETR 610 Triple: [Trenitalia, fleet, ETR 610]
Generated description
The ETR 610 is a high-speed tilting electric multiple unit train used on international and domestic services in Italy and neighboring countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ETR 610 Target entity description: The ETR 610 is a high-speed tilting electric multiple unit train used on international and domestic services in Italy and neighboring countries.
-
A.
ETD
ETD is the ICAO airline designator used to identify Etihad Airways in international aviation operations and communications.
-
B.
E313
E313 is a major Belgian motorway connecting Antwerp with Liège and serving as a key east–west transport corridor through the Limburg region.
-
C.
ETM
ETM is the IATA airport code for Ramon Airport, an international airport serving the Eilat region in southern Israel.
-
D.
ETM
ETM is the stock ticker symbol for Audacy, Inc., a major American radio broadcasting and digital audio company formerly known as Entercom Communications.
-
E.
ETU
ETU is the commonly used abbreviation for Erzurum Technical University, a public higher education institution located in Erzurum, Turkey.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084d11148190919eef8e55569bb9 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5f9a0708190bc429692788a63d7 |
completed | May 9, 2026, 7:44 a.m. |
| NEDg | Description generation | batch_69fee6b1a29481908c5c945ef801468d |
completed | May 9, 2026, 7:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fee7b5e3f0819091246455e239996a |
completed | May 9, 2026, 7:52 a.m. |
Created at: April 10, 2026, 3:13 a.m.