Triple
T14381830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Sagunto |
E356620
|
entity |
| Predicate | UNLOCODE |
P1800
|
FINISHED |
| Object |
ESSAG
ESSAG is the UN/LOCODE identifier for the Port of Sagunto, a maritime port located near Valencia on Spain’s Mediterranean coast.
|
E1094690
|
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: ESSAG | Statement: [Port of Sagunto, UNLOCODE, ESSAG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ESSAG Context triple: [Port of Sagunto, UNLOCODE, ESSAG]
-
A.
Eaton’s
Eaton’s was a major Canadian department store chain that became a retail icon and helped shape downtown shopping districts across the country.
-
B.
Cegelec
Cegelec is an international engineering and technology services company specializing in electrical, automation, and information systems for infrastructure and industry.
-
C.
Enasa
Enasa was a Spanish state-owned automotive manufacturer best known for producing Pegaso commercial vehicles and trucks.
-
D.
Enneco
Enneco is a medieval Basque given name, historically associated with early Navarrese nobility and considered an antecedent of the name Íñigo.
-
E.
Egis Group
Egis Group is a global engineering and infrastructure consulting firm that manages and operates transportation facilities such as airports, roads, and urban transit systems.
- 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: ESSAG Triple: [Port of Sagunto, UNLOCODE, ESSAG]
Generated description
ESSAG is the UN/LOCODE identifier for the Port of Sagunto, a maritime port located near Valencia on Spain’s Mediterranean coast.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ESSAG Target entity description: ESSAG is the UN/LOCODE identifier for the Port of Sagunto, a maritime port located near Valencia on Spain’s Mediterranean coast.
-
A.
Eaton’s
Eaton’s was a major Canadian department store chain that became a retail icon and helped shape downtown shopping districts across the country.
-
B.
Cegelec
Cegelec is an international engineering and technology services company specializing in electrical, automation, and information systems for infrastructure and industry.
-
C.
Enasa
Enasa was a Spanish state-owned automotive manufacturer best known for producing Pegaso commercial vehicles and trucks.
-
D.
Enneco
Enneco is a medieval Basque given name, historically associated with early Navarrese nobility and considered an antecedent of the name Íñigo.
-
E.
Egis Group
Egis Group is a global engineering and infrastructure consulting firm that manages and operates transportation facilities such as airports, roads, and urban transit systems.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de900bbfb08190a1e56f281a2374c0 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c5a7ab4819090ad0ba45f4ddba9 |
completed | May 8, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fd4d25f1e08190b78205d84ea8b7d7 |
completed | May 8, 2026, 2:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4da8af2c8190ad3e78bbe1c9cd7a |
completed | May 8, 2026, 2:42 a.m. |
Created at: April 10, 2026, 1:16 a.m.