Triple
T2513430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorenz Hackenholt |
E52752
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Lorenz
Lorenz is a masculine given name of German origin, historically borne by various notable figures in Europe.
|
E275141
|
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: Lorenz | Statement: [Lorenz Hackenholt, givenName, Lorenz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorenz Context triple: [Lorenz Hackenholt, givenName, Lorenz]
-
A.
Lindemann
Lindemann is a German surname most notably associated with Ferdinand von Lindemann, the mathematician who proved that π is a transcendental number.
-
B.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
C.
Saffman
Saffman is a surname most notably associated with Philip G. Saffman, a prominent British-American applied mathematician and fluid dynamicist.
-
D.
Dynamo
Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
-
E.
Le Niêsant
Le Niêsant is a small islet within the Les Minquiers reef and island group in the Channel Islands, known for its remote, tidal environment.
- 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: Lorenz Triple: [Lorenz Hackenholt, givenName, Lorenz]
Generated description
Lorenz is a masculine given name of German origin, historically borne by various notable figures in Europe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lorenz Target entity description: Lorenz is a masculine given name of German origin, historically borne by various notable figures in Europe.
-
A.
Lindemann
Lindemann is a German surname most notably associated with Ferdinand von Lindemann, the mathematician who proved that π is a transcendental number.
-
B.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
C.
Saffman
Saffman is a surname most notably associated with Philip G. Saffman, a prominent British-American applied mathematician and fluid dynamicist.
-
D.
Dynamo
Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
-
E.
Le Niêsant
Le Niêsant is a small islet within the Les Minquiers reef and island group in the Channel Islands, known for its remote, tidal environment.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b934d3c81909627a5f4d6e6ca6a |
completed | March 9, 2026, 8:20 p.m. |
| NEDg | Description generation | batch_69af4fd4f2a4819094b630cef9bfd8c4 |
completed | March 9, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af502a3c5c819087d3e5798db53c38 |
completed | March 9, 2026, 10:56 p.m. |
Created at: March 6, 2026, 9:46 p.m.